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ORCIDJulia A. Schnabel
Julia Anne Schnabel
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- affiliation: King's College London, UK
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2020 – today
- 2025
[i83]Veronika Spieker, Hannah Eichhorn, Wenqi Huang, Jonathan K. Stelter, Tabita Catalán, Rickmer F. Braren, Daniel Rueckert, Francisco Sahli Costabal, Kerstin Hammernik, Dimitrios C. Karampinos, Claudia Prieto, Julia A. Schnabel:
PISCO: Self-Supervised k-Space Regularization for Improved Neural Implicit k-Space Representations of Dynamic MRI. CoRR abs/2501.09403 (2025)- [i82]Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik, Elisa Saks, Lina Felsner, Kilian Weiss, Christine Preibisch, Julia A. Schnabel:
Motion-Robust T2* Quantification from Gradient Echo MRI with Physics-Informed Deep Learning. CoRR abs/2502.17209 (2025) - [i81]Jun Li, Che Liu, Wenjia Bai, Rossella Arcucci, Cosmin I. Bercea, Julia A. Schnabel:
Enhancing Abnormality Grounding for Vision Language Models with Knowledge Descriptions. CoRR abs/2503.03278 (2025) - [i80]Maxime Di Folco, Emily Chan, Marta Hasny, Cosmin I. Bercea, Julia A. Schnabel:
Semantic Alignment of Unimodal Medical Text and Vision Representations. CoRR abs/2503.04478 (2025) - [i79]Marta Hasny, Maxime Di Folco, Keno Bressem, Julia A. Schnabel:
TGV: Tabular Data-Guided Learning of Visual Cardiac Representations. CoRR abs/2503.14998 (2025) - 2024
- [j56]Inês Machado
, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King:
A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. IEEE Trans. Biomed. Eng. 71(3): 855-865 (2024) - [j55]Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel:
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. IEEE Trans. Medical Imaging 43(2): 846-859 (2024) - [c169]Varsha Raveendran, Veronika Spieker, Rickmer F. Braren, Dimitrios C. Karampinos, Veronika A. Zimmer, Julia A. Schnabel:
Segmentation-guided Medical Image Registration - Quality Awareness using Label Noise Correctionn. Bildverarbeitung für die Medizin 2024: 33-38 - [c168]Josh Stein, Maxime Di Folco, Julia A. Schnabel:
Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI Segmentation. Bildverarbeitung für die Medizin 2024: 54-59 - [c167]Tomás Chobola, Yu Liu, Hanyi Zhang, Julia A. Schnabel, Tingying Peng:
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations. ECCV (86) 2024: 413-430 - [c166]Alex Grafton, Alejandra Castelblanco, Joana M. Warnecke, Lynn Thomson, Benjamin Schubert, Anne Hilgendorff, Julia A. Schnabel, Joan Lasenby, Kathryn Beardsall:
Advancing Neonatal Care: A Deep Learning Approach for Non-Contact Heart Rate Monitoring. HealthCom 2024: 1-6 - [c165]Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang, Maxime Di Folco, Sarah C. Foreman, Verena K. N. Rösner, Ann-Kathrin Lohse, Carolin Mogler, Carolin Knebel, Marcus R. Makowski, Klaus Woertler, Stephanie E. Combs, Alexandra S. Gersing, Jan C. Peeken, Julia A. Schnabel:
Unifying Local and Global Shape Descriptors to Grade Soft-Tissue Sarcomas Using Graph Convolutional Networks. ISBI 2024: 1-5 - [c164]Benedikt Roth, Valentin Koch, Sophia J. Wagner, Julia A. Schnabel, Carsten Marr, Tingying Peng:
Low-Resource Finetuning of Foundation Models Beats State-of-the-Art in Histopathology. ISBI 2024: 1-5 - [c163]Johannes Kiechle, Daniel Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel:
Graph Neural Networks: A Suitable Alternative to MLPs in Latent 3D Medical Image Classification? GRAIL@MICCAI 2024: 12-22 - [c162]Richard Osuala, Daniel Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Enhancing the Utility of Privacy-Preserving Cancer Classification Using Synthetic Data. Deep-Breath@MICCAI 2024: 54-64 - [c161]Hassan Rasheed, Reuben Dorent, Maximilian Fehrentz, Tina Kapur, William M. Wells III, Alexandra J. Golby, Sarah F. Frisken, Julia A. Schnabel, Nazim Haouchine:
Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound. ASMUS@MICCAI 2024: 78-87 - [c160]Jun Li, Su Hwan Kim, Philip Müller, Lina Felsner, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
Language Models Meet Anomaly Detection for Better Interpretability and Generalizability. LDTM/MMMI/ML4MHD/ML-CDS@MICCAI 2024: 113-123 - [c159]Deniz Daum, Richard Osuala, Anneliese Riess, Georgios Kaissis, Julia A. Schnabel, Maxime Di Folco:
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models. DGM4MICCAI@MICCAI 2024: 139-149 - [c158]Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
MedEdit: Counterfactual Diffusion-Based Image Editing on Brain MRI. SASHIMI@MICCAI 2024: 167-176 - [c157]Anneliese Riess, Alexander Ziller, Stefan Kolek, Daniel Rueckert, Julia A. Schnabel, Georgios Kaissis:
Complex-Valued Federated Learning with Differential Privacy and MRI Applications. ISIC/iMIMIC/EARTH/DeCaF@MICCAI 2024: 191-203 - [c156]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Diffusion Models with Implicit Guidance for Medical Anomaly Detection. MICCAI (11) 2024: 211-220 - [c155]Hanna Mykula, Lisa Gasser, Silvia Lobmaier, Julia A. Schnabel, Veronika A. M. Zimmer, Cosmin I. Bercea:
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound. ASMUS@MICCAI 2024: 220-230 - [c154]Maxime Di Folco, Cosmin I. Bercea, Emily Chan, Julia A. Schnabel:
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. MICCAI (10) 2024: 492-501 - [c153]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. MICCAI (9) 2024: 510-520 - [c152]Valentin Koch, Sophia J. Wagner, Salome Kazeminia, Ece Sancar, Matthias Hehr, Julia A. Schnabel, Tingying Peng, Carsten Marr:
DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology. MICCAI (12) 2024: 520-530 - [c151]Hannah Eichhorn, Veronika Spieker, Kerstin Hammernik, Elisa Saks, Kilian Weiss, Christine Preibisch, Julia A. Schnabel:
Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI. MICCAI (7) 2024: 562-571 - [c150]Anna Reithmeir, Lina Felsner, Rickmer Braren, Julia A. Schnabel, Veronika A. Zimmer:
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration. MICCAI (2) 2024: 575-585 - [c149]Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rueckert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel:
Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations. MICCAI (7) 2024: 614-624 - [c148]Richard Osuala, Daniel M. Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Towards Learning Contrast Kinetics with Multi-condition Latent Diffusion Models. MICCAI (5) 2024: 713-723 - [c147]Daniel Grzech, Loïc Le Folgoc, Mohammad Farid Azampour, Athanasios Vlontzos, Ben Glocker, Nassir Navab, Julia A. Schnabel, Bernhard Kainz:
Unsupervised Similarity Learning for Image Registration with Energy-Based Models. WBIR 2024: 229-240 - [c146]Fryderyk Victor Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Inês Machado, Rickmer Braren, Daniel Rueckert, Julia A. Schnabel, Veronika A. Zimmer:
General Vision Encoder Features as Guidance in Medical Image Registration. WBIR 2024: 265-279 - [c145]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. WBIR 2024: 295-307 - [e21]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15001, Springer 2024, ISBN 978-3-031-72377-3 [contents] - [e20]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part II. Lecture Notes in Computer Science 15002, Springer 2024, ISBN 978-3-031-72068-0 [contents] - [e19]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part III. Lecture Notes in Computer Science 15003, Springer 2024, ISBN 978-3-031-72383-4 [contents] - [e18]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 15004, Springer 2024, ISBN 978-3-031-72082-6 [contents] - [e17]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part V. Lecture Notes in Computer Science 15005, Springer 2024, ISBN 978-3-031-72085-7 [contents] - [e16]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 15006, Springer 2024, ISBN 978-3-031-72088-8 [contents] - [e15]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part VII. Lecture Notes in Computer Science 15007, Springer 2024, ISBN 978-3-031-72103-8 [contents] - [e14]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part VIII. Lecture Notes in Computer Science 15008, Springer 2024, ISBN 978-3-031-72110-6 [contents] - [e13]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part IX. Lecture Notes in Computer Science 15009, Springer 2024, ISBN 978-3-031-72113-7 [contents] - [e12]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part X. Lecture Notes in Computer Science 15010, Springer 2024, ISBN 978-3-031-72116-8 [contents] - [e11]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part XI. Lecture Notes in Computer Science 15011, Springer 2024, ISBN 978-3-031-72119-9 [contents] - [e10]Marius George Linguraru, Qi Dou, Aasa Feragen, Stamatia Giannarou, Ben Glocker, Karim Lekadir, Julia A. Schnabel:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part XII. Lecture Notes in Computer Science 15012, Springer 2024, ISBN 978-3-031-72389-6 [contents] - [e9]Andreas K. Maier, Julia A. Schnabel, Pallavi Tiwari, Oliver Stegle:
Machine Learning for Multimodal Healthcare Data - First International Workshop, ML4MHD 2023, Honolulu, Hawaii, USA, July 29, 2023, Proceedings. Lecture Notes in Computer Science 14315, Springer 2024, ISBN 978-3-031-47678-5 [contents] - [i78]Benedikt Roth, Valentin Koch, Sophia J. Wagner, Julia A. Schnabel, Carsten Marr, Tingying Peng:
Low-resource finetuning of foundation models beats state-of-the-art in histopathology. CoRR abs/2401.04720 (2024) - [i77]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Towards Universal Unsupervised Anomaly Detection in Medical Imaging. CoRR abs/2401.10637 (2024) - [i76]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Diffusion Models with Implicit Guidance for Medical Anomaly Detection. CoRR abs/2403.08464 (2024) - [i75]Richard Osuala, Daniel Lang, Preeti Verma, Smriti Joshi, Apostolia Tsirikoglou, Grzegorz Skorupko, Kaisar Kushibar, Lidia Garrucho, Walter H. L. Pinaya, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models. CoRR abs/2403.13890 (2024) - [i74]Valentin Koch, Sophia J. Wagner, Salome Kazeminia, Ece Sancar, Matthias Hehr, Julia A. Schnabel, Tingying Peng, Carsten Marr:
DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology. CoRR abs/2404.05022 (2024) - [i73]Jun Li, Cosmin I. Bercea, Philip Müller, Lina Felsner, Su Hwan Kim, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel:
Multi-Image Visual Question Answering for Unsupervised Anomaly Detection. CoRR abs/2404.07622 (2024) - [i72]Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rückert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel:
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation. CoRR abs/2404.08350 (2024) - [i71]Maxime Di Folco, Cosmin I. Bercea, Julia A. Schnabel:
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. CoRR abs/2406.08282 (2024) - [i70]Stefan M. Fischer, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge. CoRR abs/2406.14365 (2024) - [i69]Jack Highton, Quok Zong Chong, Samuel Finestone, Arian Beqiri, Julia A. Schnabel, Kanwal K. Bhatia:
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation. CoRR abs/2406.19557 (2024) - [i68]Mehmet Yigit Avci, Emily Chan, Veronika A. M. Zimmer, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders. CoRR abs/2407.03863 (2024) - [i67]Anna Reithmeir, Lina Felsner, Rickmer Braren, Julia A. Schnabel, Veronika A. Zimmer:
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration. CoRR abs/2407.04355 (2024) - [i66]Reza Nasirigerdeh, Nader Razmi, Julia A. Schnabel, Daniel Rueckert, Georgios Kaissis:
Machine Unlearning for Medical Imaging. CoRR abs/2407.07539 (2024) - [i65]Stefan M. Fischer, Lina Felsner, Richard Osuala, Johannes Kiechle, Daniel M. Lang, Jan C. Peeken, Julia A. Schnabel:
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks. CoRR abs/2407.07853 (2024) - [i64]Tomás Chobola, Yu Liu, Hanyi Zhang, Julia A. Schnabel, Tingying Peng:
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations. CoRR abs/2407.12511 (2024) - [i63]Richard Osuala, Daniel M. Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Díaz, Julia A. Schnabel, Karim Lekadir:
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data. CoRR abs/2407.12669 (2024) - [i62]Fryderyk Victor Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Inês Machado, Rickmer Braren, Daniel Rückert, Julia A. Schnabel, Veronika A. Zimmer:
General Vision Encoder Features as Guidance in Medical Image Registration. CoRR abs/2407.13311 (2024) - [i61]Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI. CoRR abs/2407.15270 (2024) - [i60]Deniz Daum, Richard Osuala, Anneliese Riess, Georgios Kaissis, Julia A. Schnabel, Maxime Di Folco:
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models. CoRR abs/2407.16405 (2024) - [i59]Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin:
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer. CoRR abs/2407.17114 (2024) - [i58]Johannes Kiechle, Daniel M. Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel:
Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification? CoRR abs/2407.17219 (2024) - [i57]Reuben Dorent, Roya Khajavi, Tagwa Idris, Erik Ziegler, Bhanusupriya Somarouthu, Heather Jacene, Ann S. LaCasce, Jonathan Deissler, Jan Ehrhardt, Sofija Engelson, Stefan M. Fischer, Yun Gu, Heinz Handels, Satoshi Kasai, Satoshi Kondo, Klaus H. Maier-Hein, Julia A. Schnabel, Guotai Wang, Litingyu Wang, Tassilo Wald, Guang-Zhong Yang, Hanxiao Zhang, Minghui Zhang, Steven D. Pieper, Gordon J. Harris, Ron Kikinis, Tina Kapur:
LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification. CoRR abs/2408.10069 (2024) - [i56]Hassan Rasheed, Reuben Dorent, Maximilian Fehrentz, Tina Kapur, William M. Wells III, Alexandra J. Golby, Sarah F. Frisken, Julia A. Schnabel, Nazim Haouchine:
Learning to Match 2D Keypoints Across Preoperative MR and Intraoperative Ultrasound. CoRR abs/2409.08169 (2024) - [i55]Valentin Koch, Sabine Bauer, Valerio Lupperger, Michael Joner, Heribert Schunkert, Julia A. Schnabel, Moritz von Scheidt, Carsten Marr:
UNICORN: A Deep Learning Model for Integrating Multi-Stain Data in Histopathology. CoRR abs/2409.17775 (2024) - [i54]Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, Lidia Garrucho, Walter H. L. Pinaya, Daniel M. Lang, Julia A. Schnabel, Oliver Díaz, Karim Lekadir:
Simulating Dynamic Tumor Contrast Enhancement in Breast MRI using Conditional Generative Adversarial Networks. CoRR abs/2409.18872 (2024) - [i53]Sameer Ambekar, Julia A. Schnabel, Cosmin I. Bercea:
Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations. CoRR abs/2410.03306 (2024) - [i52]Cosmin I. Bercea, Philippe C. Cattin, Julia A. Schnabel, Julia Wolleb:
Denoising Diffusion Models for Anomaly Localization in Medical Images. CoRR abs/2410.23834 (2024) - [i51]Philipp Endres, Valentin Koch, Julia A. Schnabel, Carsten Marr:
CellPilot: A unified approach to automatic and interactive segmentation in histopathology. CoRR abs/2411.15514 (2024) - [i50]Wenqi Huang, Veronika Spieker, Siying Xu, Gastão Cruz, Claudia Prieto, Julia A. Schnabel, Kerstin Hammernik, Thomas Kustner, Daniel Rueckert:
Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging. CoRR abs/2412.12742 (2024) - [i49]Anna Reithmeir, Veronika Spieker, Vasiliki Sideri-Lampretsa, Daniel Rueckert, Julia A. Schnabel, Veronika A. Zimmer:
From Model Based to Learned Regularization in Medical Image Registration: A Comprehensive Review. CoRR abs/2412.15740 (2024) - 2023
- [j54]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view. Medical Image Anal. 83: 102639 (2023) - [j53]Robert Wright, Alberto Gómez, Veronika A. Zimmer, Nicolas Toussaint, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Fast fetal head compounding from multi-view 3D ultrasound. Medical Image Anal. 89: 102793 (2023) - [c144]Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Bias in Unsupervised Anomaly Detection in Brain MRI. CLIP/FAIMI/EPIMI@MICCAI 2023: 122-131 - [c143]Alejandra Castelblanco, Giusy Matzeu, Elisabetta Ruggeri, Fiorenzo G. Omenetto, Anne Hilgendorff, Julia A. Schnabel, Benjamin Schubert:
Colorimetric Sensor Reading and Illumination Correction via Multi-Task Deep-Learning. EMBC 2023: 1-5 - [c142]Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert:
A skeletonization algorithm for gradient-based optimization. ICCV 2023: 21337-21346 - [c141]Jeronimo Carvajal Maldonado, Lorenz Lamm, Ye Liu, Yu Liu, Ricardo D. Righetto, Julia A. Schnabel, Tingying Peng:
F2FD: Fourier Perturbations for Denoising Cryo-Electron Tomograms and Comparison to Established Approaches. ISBI 2023: 1-5 - [c140]Jack Highton, Quok Zong Chong, Richard Crawley, Julia A. Schnabel, Kanwal K. Bhatia:
Evaluation of Randomized Input Sampling for Explanation (RISE) for 3D XAI - Proof of Concept for Black-Box Brain-Hemorrhage Classification. MICAD 2023: 41-51 - [c139]Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, Julia A. Schnabel:
Physics-Aware Motion Simulation For T2*-Weighted Brain MRI. SASHIMI@MICCAI 2023: 42-52 - [c138]Veronika A. Zimmer, Kerstin Hammernik, Vasiliki Sideri-Lampretsa, Wenqi Huang, Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel:
Towards Generalised Neural Implicit Representations for Image Registration. DGM4MICCAI 2023: 45-55 - [c137]Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel:
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI. CaPTion@MICCAI 2023: 55-67 - [c136]Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel:
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. DGM4MICCAI 2023: 183-192 - [c135]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. MICCAI (5) 2023: 293-303 - [c134]Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel:
What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection. MICCAI (5) 2023: 304-314 - [c133]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening. MIDL 2023: 39-52 - [c132]Josh Stein, Maxime Di Folco, Julia A. Schnabel:
Sparse Annotation Strategies for Segmentation of Short Axis Cardiac MRI. STACOM@MICCAI 2023: 66-76 - [e8]Bernhard Kainz, J. Alison Noble, Julia A. Schnabel, Bishesh Khanal, Johanna P. Müller, Thomas G. Day:
Simplifying Medical Ultrasound - 4th International Workshop, ASMUS 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14337, Springer 2023, ISBN 978-3-031-44520-0 [contents] - [i48]Sophia J. Wagner, Daniel Reisenbüchler, Nicholas P. West, Jan Moritz Niehues, Gregory Patrick Veldhuizen, Philip Quirke, Heike Irmgard Grabsch, Piet A. van den Brandt, Gordon G. A. Hutchins, Susan D. Richman, Tanwei Yuan, Rupert Langer, Josien Christina Anna Jenniskens, Kelly Offermans, Wolfram Müller, Richard Gray, Stephen B. Gruber, Joel K. Greenson, Gad Rennert, Joseph D. Bonner, Daniel Schmolze, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Michael Hoffmeister, Daniel Truhn, Julia A. Schnabel, Melanie Boxberg, Tingying Peng, Jakob Nikolas Kather:
Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. CoRR abs/2301.09617 (2023) - [i47]Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel:
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. CoRR abs/2303.08452 (2023) - [i46]Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel:
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. CoRR abs/2305.06739 (2023) - [i45]Cosmin I. Bercea, Michael Neumayr, Daniel Rueckert, Julia A. Schnabel:
Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models. CoRR abs/2305.19643 (2023) - [i44]Josh Stein, Maxime Di Folco, Julia A. Schnabel:
Sparse annotation strategies for segmentation of short axis cardiac MRI. CoRR abs/2307.12619 (2023) - [i43]Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel:
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. CoRR abs/2308.08830 (2023) - [i42]Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Bias in Unsupervised Anomaly Detection in Brain MRI. CoRR abs/2308.13861 (2023) - [i41]Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer, Suprosanna Shit, Ivan Ezhov, Robbie Holland, Monika Probst, Julia A. Schnabel, Daniel Rueckert:
A skeletonization algorithm for gradient-based optimization. CoRR abs/2309.02527 (2023) - [i40]Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.:
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR abs/2309.12325 (2023) - [i39]Anna Reithmeir, Julia A. Schnabel, Veronika A. Zimmer:
Learning Physics-Inspired Regularization for Medical Image Registration with Hypernetworks. CoRR abs/2311.08239 (2023) - [i38]Maxime Di Folco, Cosmin I. Bercea, Julia A. Schnabel:
Attribute Regularized Soft Introspective Variational Autoencoder for Interpretable Cardiac Disease Classification. CoRR abs/2312.08915 (2023) - [i37]Josh Stein, Maxime Di Folco, Julia A. Schnabel:
Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI segmentation. CoRR abs/2312.08932 (2023) - 2022
- [j52]Natasha Stephenson, Kuberan Pushparajah, Gavin Wheeler, Shujie Deng, Julia A. Schnabel, John M. Simpson:
Evaluation of a Linear Measurement Tool in Virtual Reality for Assessment of Multimodality Imaging Data - A Phantom Study. J. Imaging 8(11): 304 (2022) - [j51]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
AtrialJSQnet: A New framework for joint segmentation and quantification of left atrium and scars incorporating spatial and shape information. Medical Image Anal. 76: 102303 (2022) - [j50]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
Medical image analysis on left atrial LGE MRI for atrial fibrillation studies: A review. Medical Image Anal. 77: 102360 (2022) - [j49]James R. Clough, Nicholas Byrne, Ilkay Öksüz, Veronika A. Zimmer, Julia A. Schnabel, Andrew P. King:
A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8766-8778 (2022) - [j48]Alberto Gómez, Veronika A. Zimmer, Gavin Wheeler, Nicolas Toussaint, Shujie Deng, Robert Wright, Emily Skelton, Jackie Matthews, Bernhard Kainz, Joseph V. Hajnal, Julia A. Schnabel:
PRETUS: A plug-in based platform for real-time ultrasound imaging research. SoftwareX 17: 100959 (2022) - [c131]Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia A. Schnabel, Nassir Navab, Bernhard Kainz, Loïc Le Folgoc:
A variational Bayesian method for similarity learning in non-rigid image registration. CVPR 2022: 119-128 - [c130]Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Philip J. Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón:
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. STACOM@MICCAI 2022: 101-111 - [e7]Alessa Hering, Julia A. Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias P. Heinrich, Daniel Rueckert:
Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings. Lecture Notes in Computer Science 13386, Springer 2022, ISBN 978-3-031-11202-7 [contents] - [i36]Inês Prata Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King:
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. CoRR abs/2205.01673 (2022) - [i35]Cosmin I. Bercea, Daniel Rueckert, Julia A. Schnabel:
What do we learn? Debunking the Myth of Unsupervised Outlier Detection. CoRR abs/2206.03698 (2022) - [i34]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Robert Wright, Gavin Wheeler, Shujie Deng, Nooshin Ghavami, Karen Lloyd, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View. CoRR abs/2206.14746 (2022) - [i33]Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez, Marwenie Petalcorin, Jorge Mariscal Harana, Haotian Gu, Raymond J. Kim, Robert M. Judd, Philip J. Chowienczyk, Julia A. Schnabel, Reza Razavi, Andrew P. King, Bram Ruijsink, Esther Puyol-Antón:
Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. CoRR abs/2209.14212 (2022) - 2021
- [j47]Shujie Deng, Gavin Wheeler, Nicolas Toussaint, Lindsay Munroe, Suryava Bhattacharya, Gina Sajith, Ei Lin, Eeshar Singh, Ka Yee Kelly Chu, Saleha Kabir, Kuberan Pushparajah, John M. Simpson, Julia A. Schnabel, Alberto Gómez:
A Virtual Reality System for Improved Image-Based Planning of Complex Cardiac Procedures. J. Imaging 7(8): 151 (2021) - [c129]Octavio E. Martinez Manzanera, Sam Ellis, Vasileios Baltatzis, Arjun Nair, Loïc Le Folgoc, Sujal Desai, Ben Glocker, Julia A. Schnabel:
Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data. ISBI 2021: 5-9 - [c128]Emily Chan, Matt Kelly, Julia A. Schnabel:
Comparison of Classical Machine Learning & Deep Learning to Characterise Fibrosis & Inflammation Using Quantitative MRI. ISBI 2021: 729-732 - [c127]Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel:
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. iMIMIC/TDA4MedicalData@MICCAI 2021: 56-64 - [c126]Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel:
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. PRIME@MICCAI 2021: 201-211 - [c125]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-center LGE MRIs. MICCAI (6) 2021: 557-566 - [c124]Lindsay Munroe, Gina Sajith, Ei Lin, Surjava Bhattacharya, Kuberan Pushparajah, John M. Simpson, Julia A. Schnabel, Gavin Wheeler, Alberto Gómez, Shujie Deng:
Automatic Re-orientation of 3D Echocardiographic Images in Virtual Reality Using Deep Learning. MIUA 2021: 177-188 - [c123]Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King:
Quality-Aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled K-Space Data. STACOM@MICCAI 2021: 12-20 - [c122]Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel:
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. STACOM@MICCAI 2021: 57-65 - [e6]Aasa Feragen, Stefan Sommer, Julia A. Schnabel, Mads Nielsen:
Information Processing in Medical Imaging - 27th International Conference, IPMI 2021, Virtual Event, June 28-June 30, 2021, Proceedings. Lecture Notes in Computer Science 12729, Springer 2021, ISBN 978-3-030-78190-3 [contents] - [e5]Islem Rekik, Ehsan Adeli, Sang Hyun Park, Julia A. Schnabel:
Predictive Intelligence in Medicine - 4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 12928, Springer 2021, ISBN 978-3-030-87601-2 [contents] - [i32]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs. CoRR abs/2106.08727 (2021) - [i31]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review. CoRR abs/2106.09862 (2021) - [i30]Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker:
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data. CoRR abs/2108.00250 (2021) - [i29]Vasileios Baltatzis, Loïc Le Folgoc, Sam Ellis, Octavio E. Martinez Manzanera, Kyriaki-Margarita Bintsi, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel:
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data. CoRR abs/2108.04815 (2021) - [i28]Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel:
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification. CoRR abs/2108.05386 (2021) - [i27]Alberto Gómez, Veronika A. Zimmer, Gavin Wheeler, Nicolas Toussaint, Shujie Deng, Robert Wright, Emily Skelton, Jackie Matthews, Bernhard Kainz, Joseph V. Hajnal, Julia A. Schnabel:
PRETUS: A plug-in based platform for real-time ultrasound imaging research. CoRR abs/2109.06519 (2021) - [i26]Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King:
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data. CoRR abs/2109.07955 (2021) - [i25]Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel:
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. CoRR abs/2109.13230 (2021) - [i24]Loïc Le Folgoc, Vasileios Baltatzis, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Arjun Nair, Huaqi Qiu, Julia A. Schnabel, Ben Glocker:
Is MC Dropout Bayesian? CoRR abs/2110.04286 (2021) - 2020
- [j46]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. Proc. IEEE 108(1): 110-124 (2020) - [j45]Bartlomiej W. Papiez, Bostjan Markelc, Graham Brown, Ruth J. Muschel, Michael Brady, Julia A. Schnabel:
Image-Based Artefact Removal in Laser Scanning Microscopy. IEEE Trans. Biomed. Eng. 67(1): 79-87 (2020) - [j44]Caifeng Shan, Tao Tan, Shandong Wu, Julia A. Schnabel:
Guest Editorial: Deep Learning in Ultrasound Imaging. IEEE J. Biomed. Health Informatics 24(4): 929-930 (2020) - [j43]Yiming Xiao, Andreas Maier, Wolfgang Wein, Roozbeh Shams, Samuel Kadoury, David Drobny, Marc Modat, Ingerid Reinertsen, Hassan Rivaz, Matthieu Chabanas, Maryse Fortin, Inês Machado, Yangming Ou, Mattias P. Heinrich, Julia A. Schnabel, Xia Zhong:
Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge. IEEE Trans. Medical Imaging 39(3): 777-786 (2020) - [j42]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation. IEEE Trans. Medical Imaging 39(12): 4001-4010 (2020) - [c121]Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang:
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention. MICCAI (4) 2020: 118-127 - [c120]Lei Li, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang:
Random Style Transfer Based Domain Generalization Networks Integrating Shape and Spatial Information. M&Ms and EMIDEC/STACOM@MICCAI 2020: 208-218 - [c119]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Nooshin Ghavami, Robert Wright, Lei Li, Jacqueline Matthew, Joseph V. Hajnal, Julia A. Schnabel:
A Multi-task Approach Using Positional Information for Ultrasound Placenta Segmentation. ASMUS/PIPPI@MICCAI 2020: 264-273 - [c118]Cesare Magnetti, Veronika A. M. Zimmer, Nooshin Ghavami, Emily Skelton, Jacqueline Matthew, Karen Lloyd, Joseph V. Hajnal, Julia A. Schnabel, Alberto Gómez:
Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. MIUA 2020: 423-435 - [i23]Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang:
Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention. CoRR abs/2006.13011 (2020) - [i22]Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker:
Bayesian Sampling Bias Correction: Training with the Right Loss Function. CoRR abs/2006.13798 (2020) - [i21]Simona Treivase, Alberto Gómez, Jacqueline Matthew, Emily Skelton, Julia A. Schnabel, Nicolas Toussaint:
Screen Tracking for Clinical Translation of Live Ultrasound Image Analysis Methods. CoRR abs/2007.06272 (2020) - [i20]Lei Li, Veronika A. Zimmer, Julia A. Schnabel, Xiahai Zhuang:
AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information. CoRR abs/2008.04729 (2020) - [i19]Lei Li, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang:
Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information. CoRR abs/2008.12205 (2020)
2010 – 2019
- 2019
- [j41]Gabor Fichtinger, Julia A. Schnabel, Christos Davatzikos, Alejandro F. Frangi, Carlos Alberola-López:
IJCARS-MICCAI 2018 special issue. Int. J. Comput. Assist. Radiol. Surg. 14(9): 1461 (2019) - [j40]Adam Szmul, Tahreema N. Matin, Fergus V. Gleeson, Julia A. Schnabel, Vicente Grau, Bartlomiej W. Papiez:
Patch-based lung ventilation estimation using multi-layer supervoxels. Comput. Medical Imaging Graph. 74: 49-60 (2019) - [j39]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, James R. Clough, Gastão Cruz, Aurélien Bustin, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning. Medical Image Anal. 55: 136-147 (2019) - [j38]Julia A. Schnabel, Christos Davatzikos, Gabor Fichtinger, Alejandro F. Frangi, Carlos Alberola-López:
Special issue on MICCAI 2018. Medical Image Anal. 58 (2019) - [j37]Esther Puyol-Antón, Bram Ruijsink, Bernhard Gerber, Mihaela Silvia Amzulescu, Hélène Langet, Mathieu De Craene, Julia A. Schnabel, Paolo Piro, Andrew P. King:
Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients. IEEE Trans. Biomed. Eng. 66(4): 956-966 (2019) - [j36]Russell Bates, Benjamin Irving, Bostjan Markelc, Jakob Kaeppler, Graham Brown, Ruth J. Muschel, J. Michael Brady, Vicente Grau, Julia A. Schnabel:
Segmentation of Vasculature From Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images. IEEE Trans. Medical Imaging 38(1): 1-10 (2019) - [j35]Qingjie Meng, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz, Matthew Sinclair, Veronika A. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Ozan Oktay, Jo Schlemper, Alberto Gómez:
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging. IEEE Trans. Medical Imaging 38(12): 2755-2767 (2019) - [c117]Alberto Gómez, Cornelia Schmitz, Markus Henningsson, James Housden, Yohan Noh, Veronika A. Zimmer, James R. Clough, Ilkay Öksüz, Nicolas Toussaint, Andrew P. King, Julia A. Schnabel:
Mechanically Powered Motion Imaging Phantoms: Proof of Concept. EMBC 2019: 2723-2726 - [c116]James R. Clough, Ilkay Öksüz, Nicholas Byrne, Julia A. Schnabel, Andrew P. King:
Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology. IPMI 2019: 16-28 - [c115]Ilkay Öksüz, Gastão Cruz, James R. Clough, Aurélien Bustin, Nicolo Fuin, René M. Botnar, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
Magnetic Resonance Fingerprinting Using Recurrent Neural Networks. ISBI 2019: 1537-1540 - [c114]Eric Kerfoot, Esther Puyol-Antón, Bram Ruijsink, Rina Ariga, Ernesto Zacur, Pablo Lamata, Julia A. Schnabel:
Synthesising Images and Labels Between MR Sequence Types with CycleGAN. DART/MIL3ID@MICCAI 2019: 45-53 - [c113]Laura Dal Toso, Elisabeth Pfaehler, Ronald Boellaard, Julia A. Schnabel, Paul K. Marsden:
Deep Learning Based Approach to Quantification of PET Tracer Uptake in Small Tumors. MLMIR@MICCAI 2019: 181-192 - [c112]Alberto Gómez, Veronika A. Zimmer, Nicolas Toussaint, Robert Wright, James R. Clough, Bishesh Khanal, Milou P. M. van Poppel, Emily Skelton, Jackie Matthews, Julia A. Schnabel:
Image Reconstruction in a Manifold of Image Patches: Application to Whole-Fetus Ultrasound Imaging. MLMIR@MICCAI 2019: 226-235 - [c111]Robert Wright, Nicolas Toussaint, Alberto Gómez, Veronika A. M. Zimmer, Bishesh Khanal, Jacqueline Matthew, Emily Skelton, Bernhard Kainz, Daniel Rueckert, Joseph V. Hajnal, Julia A. Schnabel:
Complete Fetal Head Compounding from Multi-view 3D Ultrasound. MICCAI (3) 2019: 384-392 - [c110]Veronika A. Zimmer, Alberto Gómez, Emily Skelton, Nicolas Toussaint, Tong Zhang, Bishesh Khanal, Robert Wright, Yohan Noh, Alison Ho, Jacqueline Matthew, Joseph V. Hajnal, Julia A. Schnabel:
Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images. MICCAI (5) 2019: 628-636 - [c109]James R. Clough, Ilkay Öksüz, Esther Puyol-Antón, Bram Ruijsink, Andrew P. King, Julia A. Schnabel:
Global and Local Interpretability for Cardiac MRI Classification. MICCAI (4) 2019: 656-664 - [c108]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space. MICCAI (4) 2019: 695-703 - [c107]Ilkay Öksüz, James R. Clough, Wenjia Bai, Bram Ruijsink, Esther Puyol-Antón, Gastão Cruz, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
High-quality segmentation of low quality cardiac MR images using k-space artefact correction. MIDL 2019: 380-389 - [i18]James R. Clough, Ilkay Öksüz, Nicholas Byrne, Julia A. Schnabel, Andrew P. King:
Explicit topological priors for deep-learning based image segmentation using persistent homology. CoRR abs/1901.10244 (2019) - [i17]Alberto Gómez, Cornelia Schmitz, Markus Henningsson, James Housden, Yohan Noh, Veronika A. Zimmer, James R. Clough, Ilkay Öksüz, Nicolas Toussaint, Andrew P. King, Julia A. Schnabel:
Mechanically Powered Motion Imaging Phantoms: Proof of Concept. CoRR abs/1905.07198 (2019) - [i16]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Andrew P. King, Julia A. Schnabel:
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space. CoRR abs/1906.05695 (2019) - [i15]James R. Clough, Ilkay Öksüz, Esther Puyol-Antón, Bram Ruijsink, Andrew P. King, Julia A. Schnabel:
Global and Local Interpretability for Cardiac MRI Classification. CoRR abs/1906.06188 (2019) - [i14]Daniel Rueckert, Julia A. Schnabel:
Model-Based and Data-Driven Strategies in Medical Image Computing. CoRR abs/1909.10391 (2019) - [i13]Jo Schlemper, Ilkay Öksüz, James R. Clough, Jinming Duan, Andrew P. King, Julia A. Schnabel, Joseph V. Hajnal, Daniel Rueckert:
dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance. CoRR abs/1909.10995 (2019) - [i12]James R. Clough, Ilkay Öksüz, Nicholas Byrne, Veronika A. Zimmer, Julia A. Schnabel, Andrew P. King:
A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology. CoRR abs/1910.01877 (2019) - [i11]Ilkay Öksüz, James R. Clough, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation. CoRR abs/1910.05370 (2019) - 2018
- [j34]Piotr Swierczynski, Bartlomiej W. Papiez, Julia A. Schnabel, Colin B. Macdonald:
A level-set approach to joint image segmentation and registration with application to CT lung imaging. Comput. Medical Imaging Graph. 65: 58-68 (2018) - [j33]Thais Roque, Laurent Risser, Veerle Kersemans, Sean Smart, Danny Allen, Paul Kinchesh, Stuart Gilchrist, Ana L. Gomes, Julia A. Schnabel, Michael A. Chappell:
A DCE-MRI Driven 3-D Reaction-Diffusion Model of Solid Tumor Growth. IEEE Trans. Medical Imaging 37(3): 724-732 (2018) - [c106]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Matthew Sinclair, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic left ventricular outflow tract classification for accurate cardiac MR planning. ISBI 2018: 462-465 - [c105]Esther Puyol-Antón, Bram Ruijsink, Wenjia Bai, Hélène Langet, Mathieu De Craene, Julia A. Schnabel, Paolo Piro, Andrew P. King, Matthew Sinclair:
Fully automated myocardial strain estimation from cine MRI using convolutional neural networks. ISBI 2018: 1139-1143 - [c104]Hirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia A. Schnabel, Kensaku Mori:
Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images. Computer-Aided Diagnosis 2018: 1057502 - [c103]Ilkay Öksüz, James R. Clough, Aurélien Bustin, Gastão Cruz, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction. MLMIR@MICCAI 2018: 21-29 - [c102]Eric Kerfoot, Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Andrew P. King, Julia A. Schnabel:
Automated CNN-Based Reconstruction of Short-Axis Cardiac MR Sequence from Real-Time Image Data. RAMBO+BIA+TIA@MICCAI 2018: 32-41 - [c101]Qingjie Meng, Christian F. Baumgartner, Matthew Sinclair, James Housden, Martin Rajchl, Alberto Gómez, Benjamin Hou, Nicolas Toussaint, Veronika A. M. Zimmer, Jeremy Tan, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
Automatic Shadow Detection in 2D Ultrasound Images. DATRA/PIPPI@MICCAI 2018: 66-75 - [c100]Esther Puyol-Antón, Bram Ruijsink, Hélène Langet, Mathieu De Craene, Paolo Piro, Julia A. Schnabel, Andrew P. King:
Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas. STACOM@MICCAI 2018: 94-102 - [c99]Veronika A. Zimmer, Alberto Gómez, Yohan Noh, Nicolas Toussaint, Bishesh Khanal, Robert Wright, Laura Peralta Pereira, Milou P. M. van Poppel, Emily Skelton, Jacqueline Matthew, Julia A. Schnabel:
Multi-view Image Reconstruction: Application to Fetal Ultrasound Compounding. DATRA/PIPPI@MICCAI 2018: 107-116 - [c98]Bishesh Khanal, Alberto Gómez, Nicolas Toussaint, Steven McDonagh, Veronika A. M. Zimmer, Emily Skelton, Jacqueline Matthew, Daniel Grzech, Robert Wright, Chandni Gupta, Benjamin Hou, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers. DATRA/PIPPI@MICCAI 2018: 117-127 - [c97]Robert Wright, Bishesh Khanal, Alberto Gómez, Emily Skelton, Jacqueline Matthew, Joseph V. Hajnal, Daniel Rueckert, Julia A. Schnabel:
LSTM Spatial Co-transformer Networks for Registration of 3D Fetal US and MR Brain Images. DATRA/PIPPI@MICCAI 2018: 149-159 - [c96]Nicolas Toussaint, Bishesh Khanal, Matthew Sinclair, Alberto Gómez, Emily Skelton, Jacqueline Matthew, Julia A. Schnabel:
Weakly Supervised Localisation for Fetal Ultrasound Images. DLMIA/ML-CDS@MICCAI 2018: 192-200 - [c95]Hirohisa Oda, Holger R. Roth, Kosuke Chiba, Jure Sokolic, Takayuki Kitasaka, Masahiro Oda, Akinari Hinoki, Hiroo Uchida, Julia A. Schnabel, Kensaku Mori:
BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images. MICCAI (2) 2018: 228-236 - [c94]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection. MICCAI (1) 2018: 250-258 - [c93]Adam Szmul, Tahreema N. Matin, Fergus V. Gleeson, Julia A. Schnabel, Vicente Grau, Bartlomiej W. Papiez:
XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-Derived Motion Model. RAMBO+BIA+TIA@MICCAI 2018: 260-271 - [c92]Eric Kerfoot, James R. Clough, Ilkay Öksüz, Jack Lee, Andrew P. King, Julia A. Schnabel:
Left-Ventricle Quantification Using Residual U-Net. STACOM@MICCAI 2018: 371-380 - [c91]Adam Szmul, Bartlomiej W. Papiez, Tahreema N. Matin, Fergus V. Gleeson, Julia A. Schnabel, Vicente Grau:
Regional lung ventilation estimation based on supervoxel tracking. Image-Guided Procedures 2018: 105761E - [c90]Bartlomiej W. Papiez, Daniel R. McGowan, Michael Skwarski, Geoff S. Higgins, Julia A. Schnabel, J. Michael Brady:
Fast Groupwise 4D Deformable Image Registration for Irregular Breathing Motion Estimation. WBIR 2018: 37-46 - [e4]Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11070, Springer 2018, ISBN 978-3-030-00927-4 [contents] - [e3]Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II. Lecture Notes in Computer Science 11071, Springer 2018, ISBN 978-3-030-00933-5 [contents] - [e2]Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11072, Springer 2018, ISBN 978-3-030-00930-4 [contents] - [e1]Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV. Lecture Notes in Computer Science 11073, Springer 2018, ISBN 978-3-030-00936-6 [contents] - [i10]Alberto Gómez, Veronika A. Zimmer, Bishesh Khanal, Nicolas Toussaint, Julia A. Schnabel:
Oversegmenting Graphs. CoRR abs/1806.00411 (2018) - [i9]Bishesh Khanal, Alberto Gómez, Nicolas Toussaint, Steven G. McDonagh, Veronika A. Zimmer, Emily Skelton, Jacqueline Matthew, Daniel Grzech, Robert Wright, Chandni Gupta, Benjamin Hou, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers. CoRR abs/1807.10583 (2018) - [i8]Esther Puyol-Antón, Bram Ruijsink, Hélène Langet, Mathieu De Craene, Paolo Piro, Julia A. Schnabel, Andrew P. King:
Learning associations between clinical information and motion-based descriptors using a large scale MR-derived cardiac motion atlas. CoRR abs/1807.10653 (2018) - [i7]Nicolas Toussaint, Bishesh Khanal, Matthew Sinclair, Alberto Gómez, Emily Skelton, Jacqueline Matthew, Julia A. Schnabel:
Weakly Supervised Localisation for Fetal Ultrasound Images. CoRR abs/1808.00793 (2018) - [i6]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection. CoRR abs/1808.05130 (2018) - [i5]Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, James R. Clough, Gastão Cruz, Aurélien Bustin, Claudia Prieto, René M. Botnar, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning. CoRR abs/1810.12185 (2018) - [i4]Qingjie Meng, Matthew Sinclair, Veronika A. M. Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Alberto Gómez, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia A. Schnabel, Bernhard Kainz:
Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging. CoRR abs/1811.08164 (2018) - [i3]Ilkay Öksüz, Gastão Cruz, James R. Clough, Aurélien Bustin, Nicolo Fuin, René M. Botnar, Claudia Prieto, Andrew P. King, Julia A. Schnabel:
Magnetic Resonance Fingerprinting using Recurrent Neural Networks. CoRR abs/1812.08155 (2018) - 2017
- [j32]Kuangyu Shi, Fei Gao, Nassir Navab, Julia A. Schnabel, Pengcheng Shi, Sibylle Ilse Ziegler:
Editorial for the special issue of "Computational methods for molecular imaging" for computerized medical imaging and graphics. Comput. Medical Imaging Graph. 60: 1-2 (2017) - [j31]Adam Szmul, Bartlomiej W. Papiez, Andre Hallack, Vicente Grau, Julia A. Schnabel:
Supervoxels for graph cuts-based deformable image registration using guided image filtering. J. Electronic Imaging 26(6): 61607 (2017) - [c89]Hirohisa Oda, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia A. Schnabel, Kensaku Mori:
Hessian-assisted supervoxel: structure-oriented voxel clustering and application to mediastinal lymph node detection from CT volumes. Computer-Aided Diagnosis 2017: 101341D - [c88]Esther Puyol-Antón, Matthew Sinclair, Bernhard Gerber, Mihaela Silvia Amzulescu, Hélène Langet, Mathieu De Craene, Paul Aljabar, Julia A. Schnabel, Paolo Piro, Andrew P. King:
Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion. STACOM@MICCAI 2017: 3-11 - [c87]Alberto Gómez, Kanwal K. Bhatia, Sarjana Tharin, James Housden, Nicolas Toussaint, Julia A. Schnabel:
Fast Registration of 3D Fetal Ultrasound Images Using Learned Corresponding Salient Points. FIFI/OMIA@MICCAI 2017: 33-41 - [c86]Bartlomiej W. Papiez, Michael Brady, Julia A. Schnabel:
Mass Transportation for Deformable Image Registration with Application to Lung CT. CMMI/RAMBO/SWITCH@MICCAI 2017: 66-74 - [c85]Hirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Toshiaki Akita, Julia A. Schnabel, Kensaku Mori:
TBS: Tensor-Based Supervoxels for Unfolding the Heart. MICCAI (1) 2017: 681-689 - [i2]Russell Bates, Benjamin Irving, Bostjan Markelc, Jakob Kaeppler, Ruth J. Muschel, Vicente Grau, Julia A. Schnabel:
Extracting 3D Vascular Structures from Microscopy Images using Convolutional Recurrent Networks. CoRR abs/1705.09597 (2017) - 2016
- [j30]Mattias P. Heinrich, Ivor J. A. Simpson, Bartlomiej W. Papiez, Michael Brady, Julia A. Schnabel:
Deformable image registration by combining uncertainty estimates from supervoxel belief propagation. Medical Image Anal. 27: 57-71 (2016) - [j29]Benjamin Irving, James M. Franklin, Bartlomiej W. Papiez, Ewan M. Anderson, Ricky A. Sharma, Fergus V. Gleeson, Mike Brady, Julia A. Schnabel:
Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation. Medical Image Anal. 32: 69-83 (2016) - [j28]J. Michael Brady, Ralph Highnam, Benjamin Irving, Julia A. Schnabel:
Oncological image analysis. Medical Image Anal. 33: 7-12 (2016) - [j27]Julia A. Schnabel, Mattias P. Heinrich, Bartlomiej W. Papiez, J. Michael Brady:
Advances and challenges in deformable image registration: From image fusion to complex motion modelling. Medical Image Anal. 33: 145-148 (2016) - [c84]Thais Roque, Bartlomiej W. Papiez, Veerle Kersemans, Sean Smart, Danny Allen, Michael A. Chappell, Julia A. Schnabel:
Tumor Growth Estimation via Registration of DCE-MRI Derived Tumor Specific Descriptors. CVPR Workshops 2016: 507-515 - [c83]Adam Szmul, Bartlomiej W. Papiez, Russell Bates, Andre Hallack, Julia A. Schnabel, Vicente Grau:
Graph Cuts-Based Registration Revisited: A Novel Approach for Lung Image Registration Using Supervoxels and Image-Guided Filtering. CVPR Workshops 2016: 592-599 - [c82]Thais Roque, Veerle Kersemans, Sean Smart, Danny Allen, Julia A. Schnabel, Michael A. Chappell:
A DCE-MRI imaging-based model for simulation of vascular tumour growth. EMBC 2016: 5949-5952 - [c81]Siying Wang, Maria Kuklisova-Murgasova, Joseph V. Hajnal, Christian Ledig, Julia A. Schnabel:
Regression analysis for assessment of myelination status in preterm brains with magnetic resonance imaging. ISBI 2016: 278-281 - [c80]Bartlomiej W. Papiez, Adam Szmul, Vicente Grau, J. Michael Brady, Julia A. Schnabel:
Non-local Graph-Based Regularization for Deformable Image Registration. MCV/BAMBI@MICCAI 2016: 199-207 - [i1]Benjamin Irving, James M. Franklin, Bartlomiej W. Papiez, Ewan M. Anderson, Ricky A. Sharma, Fergus V. Gleeson, J. Michael Brady, Julia A. Schnabel:
Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation. CoRR abs/1604.05210 (2016) - 2015
- [j26]Ivana Isgum, Manon J. N. L. Benders, Brian B. Avants, Manuel Jorge Cardoso, Serena J. Counsell, Elda Fischi Gomez, Laura Gui, Petra S. Hüppi, Karina J. Kersbergen, Antonios Makropoulos, Andrew Melbourne, Pim Moeskops, Christian P. Mol, Maria Kuklisova-Murgasova, Daniel Rueckert, Julia A. Schnabel, Vedran Srhoj-Egekher, Jue Wu, Siying Wang, Linda S. de Vries, Max A. Viergever:
Evaluation of automatic neonatal brain segmentation algorithms: The NeoBrainS12 challenge. Medical Image Anal. 20(1): 135-151 (2015) - [j25]Ivor J. A. Simpson, Manuel Jorge Cardoso, Marc Modat, David M. Cash, Mark W. Woolrich, Jesper L. R. Andersson, Julia A. Schnabel, Sébastien Ourselin:
Probabilistic non-linear registration with spatially adaptive regularisation. Medical Image Anal. 26(1): 203-216 (2015) - [c79]Julia A. Schnabel:
Complex Motion Modelling in Cancer Imaging. Bildverarbeitung für die Medizin 2015: 1-2 - [c78]Andre Hallack, Bartlomiej W. Papiez, James M. Wilson, Lai Mun Wang, Tim Maughan, Mark J. Gooding, Julia A. Schnabel:
Correlating Tumour Histology and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptors. Patch-MI@MICCAI 2015: 137-145 - [c77]Russell Bates, Laurent Risser, Benjamin Irving, Bartlomiej W. Papiez, Pavitra Kannan, Veerle Kersemans, Julia A. Schnabel:
Filling Large Discontinuities in 3D Vascular Networks Using Skeleton- and Intensity-Based Information. MICCAI (3) 2015: 157-164 - [c76]Bartlomiej W. Papiez, Jamie Franklin, Mattias P. Heinrich, Fergus V. Gleeson, Julia A. Schnabel:
Liver Motion Estimation via Locally Adaptive Over-Segmentation Regularization. MICCAI (3) 2015: 427-434 - 2014
- [j24]Bartlomiej W. Papiez, Mattias P. Heinrich, Jérôme Fehrenbach, Laurent Risser, Julia A. Schnabel:
An implicit sliding-motion preserving regularisation via bilateral filtering for deformable image registration. Medical Image Anal. 18(8): 1299-1311 (2014) - [j23]Jieqing Jiao, Graham E. Searle, Andri C. Tziortzi, Cristian A. Salinas, Roger N. Gunn, Julia A. Schnabel:
Spatio-temporal pharmacokinetic model based registration of 4D PET neuroimaging data. NeuroImage 84: 225-235 (2014) - [c75]Monica Enescu, Mattias P. Heinrich, Esme J. Hill, Ricky A. Sharma, Michael A. Chappell, Julia A. Schnabel:
An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokinetic Parameter Estimation. BAMBI 2014: 73-84 - [c74]Elina Naydenova, Amalia Cifor, Esme J. Hill, Jamie Franklin, Ricky A. Sharma, Julia A. Schnabel:
A Semi-automated Toolkit for Analysis of Liver Cancer Treatment Response Using Perfusion CT. ABDI@MICCAI 2014: 23-32 - [c73]Mattias P. Heinrich, Bartlomiej W. Papiez, Julia A. Schnabel, Heinz Handels:
Multispectral Image Registration Based on Local Canonical Correlation Analysis. MICCAI (1) 2014: 202-209 - [c72]Benjamin Irving, Amalia Cifor, Bartlomiej W. Papiez, Jamie Franklin, Ewan M. Anderson, Michael Brady, Julia A. Schnabel:
Automated Colorectal Tumour Segmentation in DCE-MRI Using Supervoxel Neighbourhood Contrast Characteristics. MICCAI (1) 2014: 609-616 - [c71]Mattias P. Heinrich, Bartlomiej W. Papiez, Julia A. Schnabel, Heinz Handels:
Non-parametric Discrete Registration with Convex Optimisation. WBIR 2014: 51-61 - [c70]Liam Cattell, Julia A. Schnabel, Jérôme Declerck, Chloe Hutton:
Combined PET-MR Brain Registration to Discriminate between Alzheimer's Disease and Healthy Controls. WBIR 2014: 134-143 - [c69]Andre Hallack, Michael A. Chappell, Mark J. Gooding, Julia A. Schnabel:
A New Similarity Metric for Groupwise Registration of Variable Flip Angle Sequences for Improved T 10 Estimation in DCE-MRI. WBIR 2014: 154-163 - [c68]Bartlomiej W. Papiez, Thomas Tapmeier, Mattias P. Heinrich, Ruth J. Muschel, Julia A. Schnabel:
Motion Correction of Intravital Microscopy of Preclinical Lung Tumour Imaging Using Multichannel Structural Image Descriptor. WBIR 2014: 164-173 - [p1]Daniel Rueckert, Julia A. Schnabel:
Registration and Segmentation in Medical Imaging. Registration and Recognition in Images and Videos 2014: 137-156 - 2013
- [j22]Laurent Risser, François-Xavier Vialard, Habib Y. Baluwala, Julia A. Schnabel:
Piecewise-diffeomorphic image registration: Application to the motion estimation between 3D CT lung images with sliding conditions. Medical Image Anal. 17(2): 182-193 (2013) - [j21]Maria Kuklisova-Murgasova, Amalia Cifor, Raffaele Napolitano, Aris T. Papageorghiou, Gerardine Quaghebeur, Mary A. Rutherford, Joseph V. Hajnal, J. Alison Noble, Julia A. Schnabel:
Registration of 3D fetal neurosonography and MRI. Medical Image Anal. 17(8): 1137-1150 (2013) - [j20]Ivor J. A. Simpson, Mark William Woolrich, Jesper L. R. Andersson, Adrian R. Groves, Julia A. Schnabel:
Ensemble Learning Incorporating Uncertain Registration. IEEE Trans. Medical Imaging 32(4): 748-756 (2013) - [j19]Mattias P. Heinrich, Mark Jenkinson, Michael Brady, Julia A. Schnabel:
MRF-Based Deformable Registration and Ventilation Estimation of Lung CT. IEEE Trans. Medical Imaging 32(7): 1239-1248 (2013) - [j18]Amalia Cifor, Laurent Risser, Daniel Chung, Ewan M. Anderson, Julia A. Schnabel:
Hybrid Feature-Based Diffeomorphic Registration for Tumor Tracking in 2-D Liver Ultrasound Images. IEEE Trans. Medical Imaging 32(9): 1647-1656 (2013) - [c67]Carolina Wessel, Julia A. Schnabel, Michael Brady:
Realistic biomechanical model of a cancerous breast for the registration of prone to supine deformations. EMBC 2013: 7249-7252 - [c66]Mattias P. Heinrich, Mark Jenkinson, Bartlomiej W. Papiez, Fergus V. Gleeson, Michael Brady, Julia A. Schnabel:
Edge- and Detail-Preserving Sparse Image Representations for Deformable Registration of Chest MRI and CT Volumes. IPMI 2013: 463-474 - [c65]Ivor J. A. Simpson, Mark William Woolrich, Manuel Jorge Cardoso, David M. Cash, Marc Modat, Julia A. Schnabel, Sébastien Ourselin:
A Bayesian Approach for Spatially Adaptive Regularisation in Non-rigid Registration. MICCAI (2) 2013: 10-18 - [c64]Bartlomiej W. Papiez, Mattias Paul Heinrich, Laurent Risser, Julia A. Schnabel:
Complex Lung Motion Estimation via Adaptive Bilateral Filtering of the Deformation Field. MICCAI (3) 2013: 25-32 - [c63]Benjamin Irving, Lydia Tanner, Monica Enescu, Manav Bhushan, Esme J. Hill, Jamie Franklin, Ewan M. Anderson, Ricky A. Sharma, Julia A. Schnabel, Michael Brady:
Personalised Estimation of the Arterial Input Function for Improved Pharmacokinetic Modelling of Colorectal Cancer Using dceMRI. Abdominal Imaging 2013: 126-135 - [c62]Amalia Cifor, Laurent Risser, Mattias P. Heinrich, Daniel Chung, Julia A. Schnabel:
Rigid Registration of Untracked Freehand 2D Ultrasound Sweeps to 3D CT of Liver Tumours. Abdominal Imaging 2013: 155-164 - [c61]Mattias P. Heinrich, Mark Jenkinson, Bartlomiej W. Papiez, Michael Brady, Julia A. Schnabel:
Towards Realtime Multimodal Fusion for Image-Guided Interventions Using Self-similarities. MICCAI (1) 2013: 187-194 - [c60]Jieqing Jiao, Julia A. Schnabel, Roger N. Gunn:
A Generalised Spatio-Temporal Registration Framework for Dynamic PET Data: Application to Neuroreceptor Imaging. MICCAI (1) 2013: 211-218 - [c59]Manav Bhushan, Julia A. Schnabel, Michael A. Chappell, Fergus Gleeson, Mark Anderson, Jamie Franklin, Michael Brady, Mark Jenkinson:
The Impact of Heterogeneity and Uncertainty on Prediction of Response to Therapy Using Dynamic MRI Data. MICCAI (1) 2013: 316-323 - [c58]Monica Enescu, Manav Bhushan, Esme J. Hill, Jamie Franklin, Ewan M. Anderson, Ricky A. Sharma, Julia A. Schnabel:
pCT derived arterial input function for improved pharmacokinetic analysis of longitudinal dceMRI for colorectal cancer. Image Processing 2013: 86690L - 2012
- [j17]Mattias P. Heinrich, Mark Jenkinson, Manav Bhushan, Tahreema N. Matin, Fergus Gleeson, Michael Brady, Julia A. Schnabel:
MIND: Modality independent neighbourhood descriptor for multi-modal deformable registration. Medical Image Anal. 16(7): 1423-1435 (2012) - [j16]Maria Kuklisova-Murgasova, Gerardine Quaghebeur, Mary A. Rutherford, Joseph V. Hajnal, Julia A. Schnabel:
Reconstruction of fetal brain MRI with intensity matching and complete outlier removal. Medical Image Anal. 16(8): 1550-1564 (2012) - [j15]Ivor J. A. Simpson, Julia A. Schnabel, Adrian R. Groves, Jesper L. R. Andersson, Mark William Woolrich:
Probabilistic inference of regularisation in non-rigid registration. NeuroImage 59(3): 2438-2451 (2012) - [c57]Julia A. Schnabel:
Biomedical Cancer Imaging Analysis. CBMS 2012: 1-6 - [c56]Maria Kuklisova-Murgasova, Gerardine Quaghebeur, Joseph V. Hajnal, J. Alison Noble, Julia A. Schnabel:
Towards 3D registration of fetal brain MRI and ultrasound. ISBI 2012: 346-349 - [c55]Ivor J. A. Simpson, Mark William Woolrich, Jesper L. R. Andersson, Adrian R. Groves, Julia A. Schnabel:
A probabilistic non-rigid registration framework using local noise estimates. ISBI 2012: 688-691 - [c54]Amalia Cifor, Laurent Risser, Daniel Chung, Ewan M. Anderson, Julia A. Schnabel:
Hybrid feature-based Log-Demons registration for tumour tracking in 2-D liver ultrasound images. ISBI 2012: 724-727 - [c53]Laurent Risser, Mattias P. Heinrich, Tahreema N. Matin, Julia A. Schnabel:
Piecewise-diffeomorphic registration of 3D CT/MR pulmonary images with sliding conditions. ISBI 2012: 1351-1354 - [c52]Mattias P. Heinrich, Mark Jenkinson, Michael Brady, Julia A. Schnabel:
Textural mutual information based on cluster trees for multimodal deformable registration. ISBI 2012: 1471-1474 - [c51]Jieqing Jiao, Graham E. Searle, Andri C. Tziortzi, Cristian A. Salinas, Roger N. Gunn, Julia A. Schnabel:
Spatial-temporal Pharmacokinetic Model Based Registration of 4D Brain PET Data. STIA 2012: 100-112 - [c50]Mattias P. Heinrich, Mark Jenkinson, Michael Brady, Julia A. Schnabel:
Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling. MICCAI (3) 2012: 115-122 - [c49]Maria Kuklisova-Murgasova, Amalia Cifor, Raffaele Napolitano, Aris T. Papageorghiou, Gerardine Quaghebeur, J. Alison Noble, Julia A. Schnabel:
Registration of 3D Fetal Brain US and MRI. MICCAI (2) 2012: 667-674 - [c48]Jieqing Jiao, Cristian A. Salinas, Graham E. Searle, Roger N. Gunn, Julia A. Schnabel:
Joint estimation of subject motion and tracer kinetic parameters of dynamic PET data in an EM framework. Image Processing 2012: 83140A - 2011
- [j14]Jeyarajan Thiyagalingam, Daniel Goodman, Julia A. Schnabel, Anne E. Trefethen, Vicente Grau:
On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. Int. J. Biomed. Imaging 2011: 137604:1-137604:15 (2011) - [j13]Keelin Murphy, Bram van Ginneken, Joseph M. Reinhardt, Sven Kabus, Kai Ding, Xiang Deng, Kunlin Cao, Kaifang Du, Gary E. Christensen, Vincent Garcia, Tom Vercauteren, Nicholas Ayache, Olivier Commowick, Grégoire Malandain, Ben Glocker, Nikos Paragios, Nassir Navab, Vladlena Gorbunova, Jon Sporring, Marleen de Bruijne, Xiao Han, Mattias P. Heinrich, Julia A. Schnabel, Mark Jenkinson, Cristian Lorenz, Marc Modat, Jamie McClelland, Sébastien Ourselin, Sascha E. A. Muenzing, Max A. Viergever, Dante De Nigris, D. Louis Collins, Tal Arbel, Marta Peroni, Rui Li, Gregory C. Sharp, Alexander Schmidt-Richberg, Jan Ehrhardt, René Werner, Dirk Smeets, Dirk Loeckx, Gang Song, Nicholas J. Tustison, Brian B. Avants, James C. Gee, Marius Staring, Stefan Klein, Berend C. Stoel, Martin Urschler, Manuel Werlberger, Jef Vandemeulebroucke, Simon Rit, David Sarrut, Josien P. W. Pluim:
Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge. IEEE Trans. Medical Imaging 30(11): 1901-1920 (2011) - [c47]Habib Y. Baluwala, Kinda Anan Saddi, Julia A. Schnabel:
Elastic registration of chest CT images with log un-biased deformations and rigidity constraint. ISBI 2011: 1235-1238 - [c46]J. Wenjun Chi, Michael Brady, Niall Moore, Julia A. Schnabel:
Fusion of perpendicular anisotropic MRI sequences. ISBI 2011: 1455-1458 - [c45]J. Wenjun Chi, Michael Brady, Niall Moore, Julia A. Schnabel:
Segmentation of the bladder wall using coupled level set methods. ISBI 2011: 1653-1656 - [c44]Manav Bhushan, Julia A. Schnabel, Laurent Risser, Mattias P. Heinrich, J. Michael Brady, Mark Jenkinson:
Motion Correction and Parameter Estimation in dceMRI Sequences: Application to Colorectal Cancer. MICCAI (1) 2011: 476-483 - [c43]Mattias P. Heinrich, Mark Jenkinson, Manav Bhushan, Tahreema N. Matin, Fergus Gleeson, J. Michael Brady, Julia A. Schnabel:
Non-local Shape Descriptor: A New Similarity Metric for Deformable Multi-modal Registration. MICCAI (2) 2011: 541-548 - [c42]Ivor J. A. Simpson, Mark William Woolrich, Adrian R. Groves, Julia A. Schnabel:
Longitudinal Brain MRI Analysis with Uncertain Registration. MICCAI (2) 2011: 647-654 - [c41]Ziyue Wu, Maria Murgasova, Andreas Buchmann, Michael von Rhein, Julia A. Schnabel:
Brain Extraction Methods for Neonates. MIUA 2011: 111-116 - [c40]Ivor J. A. Simpson, Mark W. Woolrich, Julia A. Schnabel:
Probabilistic Segmentation Propagation from Uncertainty in Registration. MIUA 2011: 153-158 - [c39]Mattias P. Heinrich, Mark Jenkinson, J. Michael Brady, Julia A. Schnabel:
Non-rigid image registration through efficient discrete optimization. MIUA 2011: 187-192 - 2010
- [j12]Kolawole Oluwole Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
Corrigendum to "An evaluation of four automatic methods of segmenting the subcortical structures in the brain" [NeuroImage 47 (2009) 1435-1447]. NeuroImage 49(1): 1152 (2010) - [c38]Carolina Wessel, Julia A. Schnabel, Michael Brady:
Towards More Realistic Biomechanical Modelling of Tumours under Mammographic Compressions. Digital Mammography / IWDM 2010: 481-489 - [c37]Candy P. S. Ho, Christopher E. Tromans, Julia A. Schnabel, Michael Brady:
A Clustering Method for the Extraction of Microcalcifications Using Epipolar Curves in Digital Breast Tomosynthesis. Digital Mammography / IWDM 2010: 682-688 - [c36]Candy P. S. Ho, Christopher E. Tromans, Julia A. Schnabel, Michael Brady:
Microcalcification Detection in Digital Breast Tomosynthesis Using an Epipolar Curve Approach. Digital Mammography / IWDM 2010: 704-711 - [c35]Angela W. C. Lee, Julia A. Schnabel, Vijay Rajagopal, Poul M. F. Nielsen, Martyn P. Nash:
Breast Image Registration by Combining Finite Elements and Free-Form Deformations. Digital Mammography / IWDM 2010: 736-743 - [c34]Candy P. S. Ho, Christopher E. Tromans, Julia A. Schnabel, Michael Brady:
The reconstruction of microcalcification clusters in digital breast tomosynthesis. Computer-Aided Diagnosis 2010: 76241E
2000 – 2009
- 2009
- [j11]Kolawole Oluwole Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
An evaluation of four automatic methods of segmenting the subcortical structures in the brain. NeuroImage 47(4): 1435-1447 (2009) - [c33]Nathan D. Cahill, Julia A. Schnabel, J. Alison Noble, David J. Hawkes:
Overlap invariance of cumulative residual entropy measures for multimodal image alignment. Image Processing 2009: 72590I - 2008
- [j10]Andreas Mang, Julia A. Schnabel, William R. Crum, Marc Modat, Oscar Camara-Rey, Christoph Palm, Gisele Brasil-Caseiras, Hans Rolf Jäger, Sébastien Ourselin, Thorsten M. Buzug, David J. Hawkes:
Consistency of parametric registration in serial MRI studies of brain tumor progression. Int. J. Comput. Assist. Radiol. Surg. 3(3-4): 201-211 (2008) - [j9]Oscar Camara, Julia A. Schnabel, Gerard R. Ridgway, William R. Crum, Abdel Douiri, Rachael I. Scahill, Derek L. G. Hill, Nick C. Fox:
Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images. NeuroImage 42(2): 696-709 (2008) - [c32]Nathan D. Cahill, Julia A. Schnabel, J. Alison Noble, David J. Hawkes:
Revisiting overlap invariance in medical image alignment. CVPR Workshops 2008: 1-8 - [c31]Kolawole O. Babalola, Brian Patenaude, Paul Aljabar, Julia A. Schnabel, David N. Kennedy, William R. Crum, Stephen M. Smith, Timothy F. Cootes, Mark Jenkinson, Daniel Rueckert:
Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI. MICCAI (1) 2008: 409-416 - [c30]Christoph Palm, Graeme P. Penney, William R. Crum, Julia A. Schnabel, Uwe Pietrzyk, David J. Hawkes:
Fusion of rat brain histology and MRI using weighted multi-image mutual information. Image Processing 2008: 69140M - 2007
- [j8]John H. Hipwell, Christine Tanner, William R. Crum, Julia A. Schnabel, David J. Hawkes:
A New Validation Method for X-ray Mammogram Registration Algorithms Using a Projection Model of Breast X-ray Compression. IEEE Trans. Medical Imaging 26(9): 1190-1200 (2007) - [c29]Andreas Mang, Oscar Camara, Gisele Brasil-Caseiras, William R. Crum, Julia A. Schnabel, Thorsten M. Buzug, Jeremy Rees, John S. Thornton, Hans Rolf Jäger, David J. Hawkes:
Registration of Rcbv and Adc Maps with Structural and Physiological Mr Images in Glioma Patients: Study and Validation. ISBI 2007: 37-40 - [c28]Oscar Camara, Rachael I. Scahill, Julia A. Schnabel, William R. Crum, Gerard R. Ridgway, Derek L. G. Hill, Nick C. Fox:
Accuracy Assessment of Global and Local Atrophy Measurement Techniques with Realistic Simulated Longitudinal Data. MICCAI (2) 2007: 785-792 - 2006
- [j7]Oscar Camara, Martin Schweiger, Rachael I. Scahill, William R. Crum, Beatrix I. Sneller, Julia A. Schnabel, Gerard R. Ridgway, David M. Cash, Derek L. G. Hill, Nick C. Fox:
Phenomenological Model of Diffuse Global and Regional Atrophy Using Finite-Element Methods. IEEE Trans. Medical Imaging 25(11): 1417-1430 (2006) - [c27]Adam G. Chandler, Richard J. Pinder, Thomas Netsch, Julia A. Schnabel, David J. Hawkes, Derek L. G. Hill, Reza Razavi:
Correction of misaligned slices in multi-slice MR cardiac examinations by using slice-to-volume registration. ISBI 2006: 474-477 - [c26]Oscar Camara-Rey, Martin Schweiger, Rachael I. Scahill, William R. Crum, Julia A. Schnabel, Derek L. G. Hill, Nick C. Fox:
Simulation of Local and Global Atrophy in Alzheimer's Disease Studies. MICCAI (2) 2006: 937-945 - 2005
- [c25]Martin Schweiger, Oscar Camara-Rey, William R. Crum, Emma Lewis, Julia A. Schnabel, Simon R. Arridge, Derek L. G. Hill, Nick C. Fox:
An Inverse Problem Approach to the Estimation of Volume Change. MICCAI (2) 2005: 616-623 - 2004
- [j6]Graeme P. Penney, Julia A. Schnabel, Daniel Rueckert, Max A. Viergever, Wiro J. Niessen:
Registration-based interpolation. IEEE Trans. Medical Imaging 23(7): 922-926 (2004) - [c24]Graeme P. Penney, Julia A. Schnabel, Daniel Rueckert, David J. Hawkes, Wiro J. Niessen:
Registration-Based Interpolation Using a High-Resolution Image for Guidance. MICCAI (1) 2004: 558-565 - [c23]Adam Grant Chandler, Thomas Netsch, Chris A. Cocosco, Julia A. Schnabel, David J. Hawkes:
Slice-to-volume registration using mutual information between probabilistic image classifications. Image Processing 2004 - 2003
- [j5]Julia A. Schnabel, Christine Tanner, Andy D. Castellano-Smith, Andreas Degenhard, Martin O. Leach, D. Rodney Hose, Derek L. G. Hill, David J. Hawkes:
Validation of Non-Rigid Image Registration sing Finite Element Methods: Application to Breast MR Images. IEEE Trans. Medical Imaging 22(2): 238-247 (2003) - [j4]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models of the Brain using Non-Rigid Registration. IEEE Trans. Medical Imaging 22(8): 1014-1025 (2003) - [c22]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic Construction of Biventricular Statistical Shape Models. FIMH 2003: 18-29 - 2002
- [j3]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic Construction of Multiple-object Three-dimensional Statistical Shape Models: Application to Cardiac Modelling. IEEE Trans. Medical Imaging 21(9): 1151-1166 (2002) - [j2]Mark Holden, Julia A. Schnabel, Derek L. G. Hill:
Quantification of Small Cerebral Ventricular Volume Changes in Treated Growth Hormone Patients using Non-Rigid Registration. IEEE Trans. Medical Imaging 21(10): 1292-1301 (2002) - [c21]Julia A. Schnabel, Christine Tanner, Andy D. Castellano-Smith, Andreas Degenhard, Carmel Hayes, Martin O. Leach, D. Rodney Hose, Derek L. G. Hill, David J. Hawkes:
Validation of Nonrigid Registration of Contrast-Enhanced MR Mammography Using Finite Element Methods. Bildverarbeitung für die Medizin 2002: 143-146 - [c20]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models: Application to Patients with Schizophrenia. Bildverarbeitung für die Medizin 2002: 291-294 - [c19]Thomas Hartkens, Daniel Rueckert, Julia A. Schnabel, David J. Hawkes, Derek L. G. Hill:
VTK CISG Registration Toolkit: An Open Source Software Package for Affine and Nonrigid Registration of Single- and Multimodal 3D images. Bildverarbeitung für die Medizin 2002: 409-412 - [c18]Christine Tanner, Julia A. Schnabel, Andreas Degenhard, Andy D. Castellano-Smith, Carmel Hayes, Martin O. Leach, D. Rodney Hose, Derek L. G. Hill, David J. Hawkes:
Validation of Volume-Preserving Non-rigid Registration: Application to Contrast-Enhanced MR-Mammography. MICCAI (1) 2002: 307-314 - [c17]Nicholas M. I. Noble, Derek L. G. Hill, Marcel Breeuwer, Julia A. Schnabel, David J. Hawkes, Frans A. Gerritsen, Reza Razavi:
Myocardial Delineation via Registration in a Polar Coordinate System. MICCAI (1) 2002: 651-658 - [c16]Andrew D. Castellano-Smith, Thomas Hartkens, Julia Anne Schnabel, D. Rodney Hose, Haiying Liu, Walter A. Hall, Charles L. Truwit, David John Hawkes, Derek L. G. Hill:
Registration-based mesh construction technique for finite-element models of brains. Image Processing 2002 - [c15]Julia Anne Schnabel, Christine Tanner, Andrew D. Castellano-Smith, Andreas Degenhard, Carmel Hayes, Martin O. Leach, D. Rodney Hose, Derek L. G. Hill, David John Hawkes:
Finite-element based validation of nonrigid registration using single- and multilevel free-form deformations: application to contrast-enhanced MR mammography. Image Processing 2002 - [c14]Christine Tanner, Andreas Degenhard, Julia Anne Schnabel, Andrew D. Castellano-Smith, Carmel Hayes, Luke I. Sonoda, Martin O. Leach, D. Rodney Hose, Derek L. G. Hill, David John Hawkes:
Comparison of biomechanical breast models: a case study. Image Processing 2002 - 2001
- [c13]Alejandro F. Frangi, Daniel Rueckert, Julia A. Schnabel, Wiro J. Niessen:
Automatic 3D ASM Construction via Atlas-Based Landmarking and Volumetric Elastic Registration. IPMI 2001: 78-91 - [c12]Julia A. Schnabel, Christine Tanner, Andy D. Castellano-Smith, Martin O. Leach, Carmel Hayes, Andreas Degenhard, D. Rodney Hose, Derek L. G. Hill, David J. Hawkes:
Validation of Non-rigid Registration Using Finite Element Methods. IPMI 2001: 344-357 - [c11]Mark Holden, Julia A. Schnabel, Derek L. G. Hill:
Quantifying Small Changes in Brain Ventricular Volume Using Non-rigid Registration. MICCAI 2001: 49-56 - [c10]Daniel Rueckert, Alejandro F. Frangi, Julia A. Schnabel:
Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration. MICCAI 2001: 77-84 - [c9]Julia A. Schnabel, Daniel Rueckert, Marcel Quist, Jane M. Blackall, Andy D. Castellano-Smith, Thomas Hartkens, Graeme P. Penney, Walter A. Hall, Haiying Liu, Charles L. Truwit, Frans A. Gerritsen, Derek L. G. Hill, David J. Hawkes:
A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations. MICCAI 2001: 573-581 - [c8]Andy D. Castellano-Smith, Thomas Hartkens, Julia A. Schnabel, D. Rodney Hose, Haiying Liu, Walter A. Hall, Charles L. Truwit, David J. Hawkes, Derek L. G. Hill:
Constructing Patient Specific Models for Correcting Intraoperative Brain Deformation. MICCAI 2001: 1091-1098 - 2000
- [c7]Christine Tanner, Julia A. Schnabel, Daniel Chung, Matthew J. Clarkson, Daniel Rueckert, Derek L. G. Hill, David J. Hawkes:
Volume and Shape Preservation of Enhancing Lesions when Applying Non-rigid Registration to a Time Series of Contrast Enhancing MR Breast Images. MICCAI 2000: 327-337
1990 – 1999
- 1999
- [j1]Julia A. Schnabel, Simon R. Arridge:
Active shape focusing. Image Vis. Comput. 17(5-6): 419-428 (1999) - [c6]Geoffrey J. M. Parker, Julia A. Schnabel, Gareth J. Barker:
Nonlinear Smoothing of MR Images Using Approximate Entropy - A Local Measure of Signal Intensity Irregularity. IPMI 1999: 484-489 - [c5]Julia Anne Schnabel, Louis Lemieux, Udo C. Wieshmann, Simon Robert Arridge:
Measurement of hippocampal volume changes in serial MRI scans. Image Processing 1999 - 1997
- [c4]Julia A. Schnabel, Simon R. Arridge:
Multi-Scale Active Shape Description. Scale-Space 1997: 337-340 - 1996
- [c3]Julia Anne Schnabel, Simon Robert Arridge:
Multiscale shape description of MR brain images using active contour models. Image Processing 1996 - 1995
- [c2]Julia A. Schnabel, Simon R. Arridge:
Active Contour Models for Shape Description using Multiscale Differential Invariants. BMVC 1995: 1-10 - 1994
- [c1]Klaus D. Tönnies, Julia A. Schnabel:
Edge detection using the local fractal dimension. CBMS 1994: 34-39
Coauthor Index
Cosmin Bercea
aka: Cosmin I. Bercea
aka: Cosmin I. Bercea
Rickmer Braren
aka: Rickmer F. Braren
aka: Rickmer F. Braren
Andy D. Castellano-Smith
aka: Andrew D. Castellano-Smith
aka: Andrew D. Castellano-Smith
David J. Hawkes
aka: David John Hawkes
aka: David John Hawkes
Mattias P. Heinrich
aka: Mattias Paul Heinrich
aka: Mattias Paul Heinrich
Inês Machado
aka: Inês Prata Machado
aka: Inês Prata Machado
Bartlomiej Wladyslaw Papiez
aka: Bartlomiej W. Papiez
aka: Bartlomiej W. Papiez
Daniel Rueckert
aka: Daniel Rückert
aka: Daniel Rückert
[i83] [j55] [c160] [c157] [c156] [c149] [c146] [i77] [i76] [i73] [i72] [i68] [i66] [i62] [i50] [i49] [j54] [j53] [c144] [c142] [c139] [c138] [c135] [c134] [c133] [i47] [i46] [i45] [i42] [i41] [i40] [e7] [i35] [i34] [j46] [j39] [j35] [c111] [c108] [i16] [i14] [i13] [c106] [c103] [c101] [c98] [c97] [c94] [i9] [i6] [i5] [i4] [j26] [p1] [j12] [j11] [c31] [j6] [c24] [j4] [c22] [j3] [c20] [c19] [c13] [c10] [c9] [c7]
Veronika A. M. Zimmer
aka: Veronika A. Zimmer
aka: Veronika A. Zimmer
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