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2020 – today
- 2024
[j11]Jan Moritz Niehues
, Gustav Müller-Franzes, Yoni Schirris, Sophia J. Wagner, Michael Jendrusch, Matthias Kloor, Alexander T. Pearson, Hannah Sophie Muti, Katherine Jane Hewitt, Gregory Patrick Veldhuizen, Laura Zigutyte, Daniel Truhn, Jakob Nikolas Kather:
Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance. Comput. Biol. Medicine 175: 108410 (2024)- [j10]Daniel Truhn, Soroosh Tayebi Arasteh, Oliver Lester Saldanha, Gustav Müller-Franzes, Firas Khader, Philip Quirke, Nicholas P. West, Richard Gray, Gordon G. A. Hutchins, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Alexander Brobeil, Tanwei Yuan, Jenny Chang-Claude, Michael Hoffmeister, Sebastian Foersch, Tianyu Han, Sebastian Keil, Maximilian Schulze-Hagen, Peter Isfort, Philipp Bruners, Georgios Kaissis, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather:
Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. 92: 103059 (2024) - [j9]Felix Busch, Jakob Nikolas Kather, Christian Johner, Marina Moser, Daniel Truhn, Lisa C. Adams, Keno K. Bressem:
Navigating the European Union Artificial Intelligence Act for Healthcare. npj Digit. Medicine 7(1) (2024) - [j8]Isabella C. Wiest, Dyke Ferber, Jiefu Zhu, Marko van Treeck, Sonja K. Meyer, Radhika Juglan, Zunamys I. Carrero, Daniel Paech, Jens Kleesiek, Matthias P. Ebert, Daniel Truhn, Jakob Nikolas Kather:
Privacy-preserving large language models for structured medical information retrieval. npj Digit. Medicine 7(1) (2024) - [j7]Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard, He Wang, Hongyi Sun, Firas Khader, Daniel Truhn, Temirgali Aimyshev, Yerkebulan Zhanibekuly, Tien-Dung Le, Adrian Galdran, Miguel Ángel González Ballester, Gustavo Carneiro, Devika R. G, Hrishikesh Panikkasseril Sethumadhavan, Densen Puthussery, Hong Liu, Zekang Yang, Satoshi Kondo, Satoshi Kasai, Edward Wang, Ashritha Durvasula, Jónathan Heras, Miguel Ángel Zapata, Teresa Araújo, Guilherme Aresta, Hrvoje Bogunovic, Mustafa Arikan, Yeong Chan Lee, Hyun Bin Cho, Yoon Ho Choi, Abdul Qayyum, Imran Razzak, Bram van Ginneken, Hans G. Lemij, Clara I. Sánchez:
AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge. IEEE Trans. Medical Imaging 43(1): 542-557 (2024) - [c20]Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather:
Joint Multi-task Learning Improves Weakly-Supervised Biomarker Prediction in Computational Pathology. MICCAI (4) 2024: 254-262 - [c19]Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn:
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. MICCAI (7) 2024: 509-517 - [i41]Lisa Adams, Felix Busch, Tianyu Han, Jean-Baptiste Excoffier, Matthieu Ortala, Alexander Löser, Hugo J. W. L. Aerts, Jakob Nikolas Kather, Daniel Truhn, Keno K. Bressem:
LongHealth: A Question Answering Benchmark with Long Clinical Documents. CoRR abs/2401.14490 (2024) - [i40]Patrick Wienholt, Alexander Hermans, Firas Khader, Behrus Puladi, Bastian Leibe, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
An Ordinal Regression Framework for a Deep Learning Based Severity Assessment for Chest Radiographs. CoRR abs/2402.05685 (2024) - [i39]Omar S. M. El Nahhas, Georg Wölflein, Marta Ligero, Tim Lenz, Marko van Treeck, Firas Khader, Daniel Truhn, Jakob Nikolas Kather:
Joint multi-task learning improves weakly-supervised biomarker prediction in computational pathology. CoRR abs/2403.03891 (2024) - [i38]Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather:
In-context learning enables multimodal large language models to classify cancer pathology images. CoRR abs/2403.07407 (2024) - [i37]Dyke Ferber, Omar S. M. El Nahhas, Georg Wölflein, Isabella C. Wiest, Jan Clusmann, Marie-Elisabeth Leßman, Sebastian Foersch, Jacqueline Lammert, Maximilian Tschochohei, Dirk Jäger, Manuel Salto-Tellez, Nikolaus Schultz, Daniel Truhn, Jakob Nikolas Kather:
Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology. CoRR abs/2404.04667 (2024) - [i36]Hartmut Häntze, Lina Xu, Felix J. Dorfner, Leonhard Donle, Daniel Truhn, Hugo J. W. L. Aerts, Mathias Prokop, Bram van Ginneken, Alessa Hering, Lisa C. Adams, Keno K. Bressem:
MRSegmentator: Robust Multi-Modality Segmentation of 40 Classes in MRI and CT Sequences. CoRR abs/2405.06463 (2024) - [i35]Firas Khader, Omar S. M. El Nahhas, Tianyu Han, Gustav Müller-Franzes, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization. CoRR abs/2406.01314 (2024) - [i34]Tianyu Han, Sven Nebelung, Firas Khader, Jakob Nikolas Kather, Daniel Truhn:
On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction. CoRR abs/2406.16983 (2024) - [i33]Dyke Ferber, Lars Hilgers, Isabella C. Wiest, Marie-Elisabeth Leßmann, Jan Clusmann, Peter Neidlinger, Jiefu Zhu, Georg Wölflein, Jacqueline Lammert, Maximilian Tschochohei, Heiko Böhme, Dirk Jäger, Mihaela Aldea, Daniel Truhn, Christiane Höper, Jakob Nikolas Kather:
End-To-End Clinical Trial Matching with Large Language Models. CoRR abs/2407.13463 (2024) - [i32]Soroosh Tayebi Arasteh, Mahshad Lotfinia, Keno K. Bressem, Robert Siepmann, Dyke Ferber, Christiane Kuhl, Jakob Nikolas Kather, Sven Nebelung, Daniel Truhn:
RadioRAG: Factual Large Language Models for Enhanced Diagnostics in Radiology Using Dynamic Retrieval Augmented Generation. CoRR abs/2407.15621 (2024) - [i31]Jan Clusmann, Dyke Ferber, Isabella C. Wiest, Carolin V. Schneider, Titus J. Brinker, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather:
Prompt Injection Attacks on Large Language Models in Oncology. CoRR abs/2407.18981 (2024) - [i30]Felix J. Dorfner, Amin Dada, Felix Busch, Marcus R. Makowski, Tianyu Han, Daniel Truhn, Jens Kleesiek, Madhumita Sushil, Jacqueline Lammert, Lisa C. Adams, Keno K. Bressem:
Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data. CoRR abs/2408.13833 (2024) - [i29]Peter Neidlinger, Omar S. M. El Nahhas, Hannah Sophie Muti, Tim Lenz, Michael Hoffmeister, Hermann Brenner, Marko van Treeck, Rupert Langer, Bastian Dislich, Hans Michael Behrens, Christoph Röcken, Sebastian Foersch, Daniel Truhn, Antonio Marra, Oliver Lester Saldanha, Jakob Nikolas Kather:
Benchmarking foundation models as feature extractors for weakly-supervised computational pathology. CoRR abs/2408.15823 (2024) - [i28]Jacqueline Lammert, Nicole Pfarr, Leonid Kuligin, Sonja Mathes, Tobias Dreyer, Luise Modersohn, Patrick Metzger, Dyke Ferber, Jakob Nikolas Kather, Daniel Truhn, Lisa Christine Adams, Keno K. Bressem, Sebastian Lange, Kristina Schwamborn, Martin Boeker, Marion Kiechle, Ulrich A. Schatz, Holger Bronger, Maximilian Tschochohei:
Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors. CoRR abs/2409.00544 (2024) - 2023
- [j6]Felix Busch, Lina Xu, Dmitry Sushko, Matthias Weidlich, Daniel Truhn, Gustav Müller-Franzes, Maurice M. Heimer, Stefan Markus Niehues, Marcus R. Makowski, Markus Hinsche, Janis Lucas Vahldiek, Hugo J. W. L. Aerts, Lisa C. Adams, Keno K. Bressem:
Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs. Comput. Methods Programs Biomed. 234: 107505 (2023) - [c18]Amin Dada, Aokun Chen, Cheng Peng, Kaleb E. Smith, Ahmad Idrissi-Yaghir, Constantin Seibold, Jianning Li, Lars Heiliger, Christoph M. Friedrich, Daniel Truhn, Jan Egger, Jiang Bian, Jens Kleesiek, Yonghui Wu:
On the Impact of Cross-Domain Data on German Language Models. EMNLP (Findings) 2023: 13801-13813 - [c17]Firas Khader, Gustav Müller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Jakob Nikolas Kather, Johannes Stegmaier, Sven Nebelung, Daniel Truhn:
Vector-Quantized Latent Flows for Medical Image Synthesis and Out-Of-Distribution Detection. ISBI 2023: 1-5 - [c16]Firas Khader, Johannes Stegmaier, Sven Nebelung, Daniel Truhn:
Multi-View Abnormality Detection in Clinical Knee MRI Studies Using Transformers. ISBI 2023: 1-4 - [c15]Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Transformers for CT Reconstruction from Monoplanar and Biplanar Radiographs. SASHIMI@MICCAI 2023: 1-10 - [c14]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. MLMI@MICCAI (2) 2023: 417-426 - [i27]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) - [i26]Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis:
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR abs/2302.01622 (2023) - [i25]Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard, He Wang, Hongyi Sun, Firas Khader, Daniel Truhn, Temirgali Aimyshev, Yerkebulan Zhanibekuly, Tien-Dung Le, Adrian Galdran, Miguel Ángel González Ballester, Gustavo Carneiro, Devika R. G, Hrishikesh P. S, Densen Puthussery, Hong Liu, Zekang Yang, Satoshi Kondo, Satoshi Kasai, Edward Wang, Ashritha Durvasula, Jónathan Heras, Miguel Ángel Zapata, Teresa Araújo, Guilherme Aresta, Hrvoje Bogunovic, Mustafa Arikan, Yeong Chan Lee, Hyun Bin Cho, Yoon Ho Choi, Abdul Qayyum, Imran Razzak, Bram van Ginneken, Hans G. Lemij, Clara I. Sánchez:
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge. CoRR abs/2302.01738 (2023) - [i24]Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander Löser, Daniel Truhn, Keno K. Bressem:
MedAlpaca - An Open-Source Collection of Medical Conversational AI Models and Training Data. CoRR abs/2304.08247 (2023) - [i23]Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff, Eva Kemmer, Firas Khader, Soroosh Tayebi Arasteh, Teresa Nolte, Jakob Nikolas Kather, Sven Nebelung, Christiane Kuhl, Daniel Truhn:
Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation. CoRR abs/2304.08972 (2023) - [i22]Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers. CoRR abs/2305.06963 (2023) - [i21]Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn:
Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs. CoRR abs/2305.06965 (2023) - [i20]Soroosh Tayebi Arasteh, Mahshad Lotfinia, Teresa Nolte, Marwin Saehn, Peter Isfort, Christiane Kuhl, Sven Nebelung, Georgios Kaissis, Daniel Truhn:
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy. CoRR abs/2306.06503 (2023) - [i19]Soroosh Tayebi Arasteh, Leo Misera, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung:
Enhancing Network Initialization for Medical AI Models Using Large-Scale, Unlabeled Natural Images. CoRR abs/2308.07688 (2023) - [i18]Soroosh Tayebi Arasteh, Tianyu Han, Mahshad Lotfinia, Christiane Kuhl, Jakob Nikolas Kather, Daniel Truhn, Sven Nebelung:
Empowering Clinicians and Democratizing Data Science: Large Language Models Automate Machine Learning for Clinical Studies. CoRR abs/2308.14120 (2023) - [i17]Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Mueller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn:
Medical Foundation Models are Susceptible to Targeted Misinformation Attacks. CoRR abs/2309.17007 (2023) - [i16]Tianyu Han, Laura Zigutyte, Luisa Huck, Marc Huppertz, Robert Siepmann, Yossi Gandelsman, Christian Blüthgen, Firas Khader, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining. CoRR abs/2309.17123 (2023) - [i15]Soroosh Tayebi Arasteh, Christiane Kuhl, Marwin-Jonathan Saehn, Peter Isfort, Daniel Truhn, Sven Nebelung:
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models. CoRR abs/2310.00757 (2023) - [i14]Amin Dada, Aokun Chen, Cheng Peng, Kaleb E. Smith, Ahmad Idrissi-Yaghir, Constantin Marc Seibold, Jianning Li, Lars Heiliger, Xi Yang, Christoph M. Friedrich, Daniel Truhn, Jan Egger, Jiang Bian, Jens Kleesiek, Yonghui Wu:
On the Impact of Cross-Domain Data on German Language Models. CoRR abs/2310.07321 (2023) - [i13]Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelovic, Jakob Nikolas Kather:
A Good Feature Extractor Is All You Need for Weakly Supervised Learning in Histopathology. CoRR abs/2311.11772 (2023) - [i12]Felix Busch, Tianyu Han, Marcus R. Makowski, Daniel Truhn, Keno K. Bressem, Lisa Adams:
From Text to Image: Exploring GPT-4Vision's Potential in Advanced Radiological Analysis across Subspecialties. CoRR abs/2311.14777 (2023) - [i11]Omar S. M. El Nahhas, Marko van Treeck, Georg Wölflein, Michaela Unger, Marta Ligero, Tim Lenz, Sophia J. Wagner, Katherine Jane Hewitt, Firas Khader, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather:
From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology. CoRR abs/2312.10944 (2023) - 2022
- [j5]Felix Duong, Michael Gadermayr, Dorit Merhof, Christiane Kuhl, Philipp Bruners, Sven H. Loosen, Christoph Roderburg, Daniel Truhn, Maximilian F. Schulze-Hagen:
Automated major psoas muscle volumetry in computed tomography using machine learning algorithms. Int. J. Comput. Assist. Radiol. Surg. 17(2): 355-361 (2022) - [j4]Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather:
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Medical Image Anal. 79: 102474 (2022) - [j3]Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather:
Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474. Medical Image Anal. 82: 102622 (2022) - [j2]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Sven Nebelung, Daniel Truhn:
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. Nat. Mac. Intell. 4(11): 1029-1039 (2022) - [j1]Jakob Nikolas Kather, Narmin Ghaffari Laleh, Sebastian Foersch, Daniel Truhn:
Medical domain knowledge in domain-agnostic generative AI. npj Digit. Medicine 5 (2022) - [c13]Justus Schock, Yu-Chia Lan, Daniel Truhn, Marcin Kopaczka, Stefan Conrad, Sven Nebelung, Dorit Merhof:
Monoplanar CT Reconstruction with GANs. IPTA 2022: 1-6 - [i10]Lisa C. Adams, Felix Busch, Daniel Truhn, Marcus R. Makowski, Hugo J. W. L. Aerts, Keno K. Bressem:
What Does DALL-E 2 Know About Radiology? CoRR abs/2209.13696 (2022) - [i9]Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baeßler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. CoRR abs/2211.03364 (2022) - [i8]Soroosh Tayebi Arasteh, Peter Isfort, Marwin Saehn, Gustav Mueller-Franzes, Firas Khader, Jakob Nikolas Kather, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels. CoRR abs/2211.13606 (2022) - [i7]Gustav Müller-Franzes, Jan Moritz Niehues, Firas Khader, Soroosh Tayebi Arasteh, Christoph Haarburger, Christiane Kuhl, Tianci Wang, Tianyu Han, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Diffusion Probabilistic Models beat GANs on Medical Images. CoRR abs/2212.07501 (2022) - [i6]Firas Khader, Gustav Mueller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Christoph Haarburger, Johannes Stegmaier, Keno K. Bressem, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Medical Diagnosis with Large Scale Multimodal Transformers: Leveraging Diverse Data for More Accurate Diagnosis. CoRR abs/2212.09162 (2022) - 2021
- [c12]Michael Gadermayr, Maximilian Ernst Tschuchnig, Laxmi Gupta, Nils Krämer, Daniel Truhn, Dorit Merhof, Burkhard Gess:
An Asymmetric Cycle-Consistency Loss For Dealing With Many-To-One Mappings In Image Translation: A Study On Thigh Mr Scans. ISBI 2021: 1182-1186 - [i5]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Volkmar Schulz, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. CoRR abs/2111.11439 (2021) - 2020
- [c11]Marcin Kopaczka, Richard Lindenpütz, Daniel Truhn, Maximilian Schulze-Hagen, Dorit Merhof:
Fully Automated Segmentation of the Psoas Major Muscle in Clinical CT Scans. Bildverarbeitung für die Medizin 2020: 55-60 - [c10]Christoph Haarburger, Justus Schock, Daniel Truhn, Philippe Weitz, Gustav Mueller-Franzes, Leon Weninger, Dorit Merhof:
Radiomic Feature Stability Analysis Based on Probabilistic Segmentations. ISBI 2020: 1188-1192 - [c9]Justus Schock, Marcin Kopaczka, Benjamin Agthe, Jie Huang, Paul Kruse, Daniel Truhn, Stefan Conrad, Gerald Antoch, Christiane Kuhl, Sven Nebelung, Dorit Merhof:
A Method for Semantic Knee Bone and Cartilage Segmentation with Deep 3D Shape Fitting Using Data from the Osteoarthritis Initiative. ShapeMI@MICCAI 2020: 85-94 - [c8]Firas Khader, Justus Schock, Daniel Truhn, Fabian Morsbach, Christoph Haarburger:
Adaptive Preprocessing for Generalization in Cardiac MR Image Segmentation. M&Ms and EMIDEC/STACOM@MICCAI 2020: 269-276 - [i4]Michael Gadermayr, Maximilian Ernst Tschuchnig, Dorit Merhof, Nils Krämer, Daniel Truhn, Burkhard Gess:
An Asymetric Cycle-Consistency Loss for Dealing with Many-to-One Mappings in Image Translation: A Study on Thigh MR Scans. CoRR abs/2004.11001 (2020) - [i3]Tianyu Han, Sven Nebelung, Federico Pedersoli, Markus Zimmermann, Maximilian Schulze-Hagen, Michael Ho, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Daniel Truhn:
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. CoRR abs/2011.13011 (2020)
2010 – 2019
- 2019
- [c7]Oliver Rippel, Daniel Truhn, Johannes Thüring, Christoph Haarburger, Christiane K. Kuhl, Dorit Merhof:
Prediction of Liver Function Based on DCE-CT. Bildverarbeitung für die Medizin 2019: 8-13 - [c6]Christoph Haarburger, Michael Baumgartner, Daniel Truhn, Mirjam Broeckmann, Hannah Schneider, Simone Schrading, Christiane Kuhl, Dorit Merhof:
Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification. MICCAI (4) 2019: 495-503 - [c5]Christoph Haarburger, Nicolas Horst, Daniel Truhn, Mirjam Broeckmann, Simone Schrading, Christiane Kuhl, Dorit Merhof:
Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks. VCBM 2019: 11-15 - [i2]Christoph Haarburger, Michael Baumgartner, Daniel Truhn, Mirjam Broeckmann, Hannah Schneider, Simone Schrading, Christiane Kuhl, Dorit Merhof:
Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification. CoRR abs/1906.06058 (2019) - [i1]Christoph Haarburger, Justus Schock, Daniel Truhn, Philippe Weitz, Leon Weninger, Dorit Merhof:
Radiomic Feature Stability Analysis based on Probabilistic Segmentations. CoRR abs/1910.05693 (2019) - 2018
- [c4]Christoph Haarburger, Peter Langenberg, Daniel Truhn, Hannah Schneider, Johannes Thüring, Simone Schrading, Christiane K. Kuhl, Dorit Merhof:
Transfer Learning for Breast Cancer Malignancy Classification based on Dynamic Contrast-Enhanced MR Images. Bildverarbeitung für die Medizin 2018: 216-221 - [c3]Christoph Haarburger, Johannes Ruther, Daniel Truhn, Simone Schrading, Daniel Bug, Christiane K. Kuhl, Dorit Merhof:
Abbreviated breast biopsy procedure by registration of craniocaudal and mediolateral breast MR images. ISBI 2018: 826-830
2000 – 2009
- 2008
- [c2]Matthias Mühlich, Daniel Truhn, Kerstin Nagel, Achim Walter, Hanno Scharr, Til Aach:
Measuring Plant Root Growth. DAGM-Symposium 2008: 497-506 - 2007
- [c1]Thomas Stehle, Daniel Truhn, Til Aach, Christian Trautwein, Jens J. W. Tischendorf:
Camera Calibration for Fish-Eye Lenses en Endoscopy with an Application to 3d Reconstruction. ISBI 2007: 1176-1179
Coauthor Index
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last updated on 2024-10-31 20:17 CET by the dblp team
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