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ORCIDMarleen de Bruijne
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- affiliation: Erasmus MC, Rotterdam, The Netherlands
- affiliation: University of Copenhagen, Denmark
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2020 – today
- 2021
[c105]Marleen de Bruijne:
Learning from Imperfect Data: Weak Labels, Shifting Domains, and Small Datasets in Medical Imaging. Bildverarbeitung für die Medizin 2021: 1- [i44]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Harm A. W. M. Tiddens, Marleen de Bruijne:
Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks. CoRR abs/2103.16328 (2021) - [i43]Gerda Bortsova, Florian Dubost, Laurens Hogeweg, Ioannis Katramados, Marleen de Bruijne:
Adversarial Heart Attack: Neural Networks Fooled to Segment Heart Symbols in Chest X-Ray Images. CoRR abs/2104.00139 (2021) - 2020
- [j47]Mingquan Lin
, He Cui, Weifu Chen, Arna van Engelen, Marleen de Bruijne, M. Reza Azarpazhooh, Seyed Mojtaba Sohrevardi, John David Spence, Bernard Chiu:
Longitudinal assessment of carotid plaque texture in three-dimensional ultrasound images based on semi-supervised graph-based dimensionality reduction and feature selection. Comput. Biol. Medicine 116: 103586 (2020) - [j46]Xueli Chen, Mingquan Lin, He Cui, Yimin Chen, Arna van Engelen, Marleen de Bruijne, M. Reza Azarpazhooh, Seyed Mojtaba Sohrevardi, Tommy W. S. Chow, John David Spence, Bernard Chiu:
Three-dimensional ultrasound evaluation of the effects of pomegranate therapy on carotid plaque texture using locality preserving projection. Comput. Methods Programs Biomed. 184: 105276 (2020) - [j45]Florian Dubost, Marleen de Bruijne, Marco Nardin, Adrian V. Dalca, Kathleen L. Donahue, Anne-Katrin Giese, Mark R. Etherton, Ona Wu, Marius de Groot, Wiro J. Niessen, Meike W. Vernooij, Natalia S. Rost, Markus D. Schirmer:
Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation. Medical Image Anal. 63: 101698 (2020) - [j44]Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio Garcia-Uceda Juarez, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Graph refinement based airway extraction using mean-field networks and graph neural networks. Medical Image Anal. 64: 101751 (2020) - [j43]Florian Dubost, Hieab Adams, Pinar Yilmaz, Gerda Bortsova, Gijs van Tulder, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Weakly supervised object detection with 2D and 3D regression neural networks. Medical Image Anal. 65: 101767 (2020) - [j42]Hakim C. Achterberg, Johan J. de Rooi, Meike W. Vernooij, Mohammad Arfan Ikram, Wiro J. Niessen, Paul H. C. Eilers, Marleen de Bruijne:
Spatially Regularized Shape Analysis of the Hippocampus Using P-Spline Based Shape Regression. IEEE J. Biomed. Health Informatics 24(3): 825-834 (2020) - [j41]Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Learning to Quantify Emphysema Extent: What Labels Do We Need? IEEE J. Biomed. Health Informatics 24(4): 1149-1159 (2020) - [j40]Ruwan B. Tennakoon, Gerda Bortsova, Silas Nyboe Ørting, Amirali K. Gostar, Mathilde M. W. Wille, Zaigham Saghir, Reza Hoseinnezhad, Marleen de Bruijne, Alireza Bab-Hadiashar:
Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem. IEEE Trans. Medical Imaging 39(4): 854-865 (2020) - [c104]Subhradeep Kayal, Florian Dubost, Harm A. W. M. Tiddens, Marleen de Bruijne:
Spectral Data Augmentation Techniques to Quantify Lung Pathology from CT-Images. ISBI 2020: 586-590 - [c103]Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul H. J. Nederkoorn, M. Eline Kooi, Aad van der Lugt, Marleen de Bruijne:
Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentation. UNSURE/GRAIL@MICCAI 2020: 32-41 - [c102]Robin Camarasa, Alexis Faure, Thomas Crozier, Daniel Bos, Marleen de Bruijne:
Uncertainty-Based Segmentation of Myocardial Infarction Areas on Cardiac MR Images. M&Ms and EMIDEC/STACOM@MICCAI 2020: 385-391 - [c101]Subhradeep Kayal, Shuai Chen, Marleen de Bruijne:
Region-of-Interest Guided Supervoxel Inpainting for Self-supervision. MICCAI (1) 2020: 500-509 - [e1]Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Hervé Lombaert, Christopher Pal:
International Conference on Medical Imaging with Deep Learning, MIDL 2020, 6-8 July 2020, Montréal, QC, Canada. Proceedings of Machine Learning Research 121, PMLR 2020 [contents] - [i42]Oliver Werner, Kimberlin M. H. van Wijnen, Wiro J. Niessen, Marius de Groot, Meike W. Vernooij, Florian Dubost, Marleen de Bruijne:
When Weak Becomes Strong: Robust Quantification of White Matter Hyperintensities in Brain MRI scans. CoRR abs/2004.05578 (2020) - [i41]Subhradeep Kayal, Florian Dubost, Harm A. W. M. Tiddens, Marleen de Bruijne:
Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images. CoRR abs/2004.11989 (2020) - [i40]Suzanne C. Wetstein, Cristina González-Gonzalo, Gerda Bortsova, Bart Liefers, Florian Dubost, Ioannis Katramados, Laurens Hogeweg, Bram van Ginneken, Josien P. W. Pluim, Marleen de Bruijne, Clara I. Sánchez, Mitko Veta:
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors. CoRR abs/2006.06356 (2020) - [i39]Soumick Chatterjee, Kartik Prabhu, Mahantesh Pattadkal, Gerda Bortsova, Florian Dubost, Hendrik Mattern, Marleen de Bruijne, Oliver Speck, Andreas Nürnberger:
DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset. CoRR abs/2006.10802 (2020) - [i38]Subhradeep Kayal, Shuai Chen, Marleen de Bruijne:
Region-of-interest guided Supervoxel Inpainting for Self-supervision. CoRR abs/2006.15186 (2020) - [i37]Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Herve Lombaert, Chris Pal:
Medical Imaging with Deep Learning: MIDL 2020 - Short Paper Track. CoRR abs/2007.02319 (2020) - [i36]Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, Harm A. W. M. Tiddens, Marleen de Bruijne:
Crowdsourcing Airway Annotations in Chest Computed Tomography Images. CoRR abs/2011.10433 (2020)
2010 – 2019
- 2019
- [j39]Florian Dubost, Hieab H. Adams, Gerda Bortsova, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI. Medical Image Anal. 51: 89-100 (2019) - [j38]Veronika Cheplygina, Marleen de Bruijne, Josien P. W. Pluim:
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis. Medical Image Anal. 54: 280-296 (2019) - [j37]Florian Dubost, Pinar Yilmaz, Hieab H. Adams, Gerda Bortsova, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Enlarged perivascular spaces in brain MRI: Automated quantification in four regions. NeuroImage 185: 534-544 (2019) - [j36]Annegreet van Opbroek, Hakim C. Achterberg, Meike W. Vernooij, Marleen de Bruijne:
Transfer Learning for Image Segmentation by Combining Image Weighting and Kernel Learning. IEEE Trans. Medical Imaging 38(1): 213-224 (2019) - [j35]Gijs van Tulder, Marleen de Bruijne:
Learning Cross-Modality Representations From Multi-Modal Images. IEEE Trans. Medical Imaging 38(2): 638-648 (2019) - [j34]Jens Petersen, Andrés M. Arias Lorza, Raghavendra Selvan, Daniel Bos, Aad van der Lugt, Jesper Johannes Holst Pedersen, Mads Nielsen, Marleen de Bruijne:
Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies. IEEE Trans. Medical Imaging 38(7): 1559-1568 (2019) - [c100]Vikram Venkatraghavan, Florian Dubost, Esther E. Bron, Wiro J. Niessen, Marleen de Bruijne, Stefan Klein:
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia. IPMI 2019: 169-180 - [c99]Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim Steenstrup Pedersen, Marleen de Bruijne:
A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. IPMI 2019: 360-371 - [c98]Chaoping Zhang, Florian Dubost, Marleen de Bruijne, Stefan Klein, Dirk H. J. Poot:
APIR-Net: Autocalibrated Parallel Imaging Reconstruction Using a Neural Network. MLMIR@MICCAI 2019: 36-46 - [c97]Florian Dubost, Benjamin Collery, Antonin Renaudier, Axel Roc, Nicolas Posocco, Wiro J. Niessen, Marleen de Bruijne:
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks. CSI@MICCAI 2019: 88-94 - [c96]Florian Dubost, Max Dünnwald, Denver Huff, Vincent Scheumann, Frank Schreiber, Meike W. Vernooij, Wiro J. Niessen, Martin Skalej, Stefanie Schreiber, Steffen Oeltze-Jafra, Marleen de Bruijne:
Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI Across Sites. OR/MLCN@MICCAI 2019: 103-111 - [c95]Kimberlin M. H. van Wijnen, Florian Dubost, Pinar Yilmaz, Mohammad Arfan Ikram, Wiro J. Niessen, Hieab H. Adams, Meike W. Vernooij, Marleen de Bruijne:
Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network. MICCAI (4) 2019: 234-242 - [c94]Florian Dubost, Gerda Bortsova, Hieab H. Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Hydranet: Data Augmentation for Regression Neural Networks. MICCAI (4) 2019: 438-446 - [c93]Shuai Chen, Gerda Bortsova, Antonio García-Uceda Juárez, Gijs van Tulder, Marleen de Bruijne:
Multi-task Attention-Based Semi-supervised Learning for Medical Image Segmentation. MICCAI (3) 2019: 457-465 - [c92]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne:
A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs. MLMI@MICCAI 2019: 583-591 - [c91]Gerda Bortsova, Florian Dubost, Laurens Hogeweg, Ioannis Katramados, Marleen de Bruijne:
Semi-supervised Medical Image Segmentation via Learning Consistency Under Transformations. MICCAI (6) 2019: 810-818 - [i35]Vikram Venkatraghavan, Florian Dubost, Esther E. Bron, Wiro J. Niessen, Marleen de Bruijne, Stefan Klein:
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia. CoRR abs/1903.03386 (2019) - [i34]Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim Steenstrup Pedersen, Marleen de Bruijne:
A cross-center smoothness prior for variational Bayesian brain tissue segmentation. CoRR abs/1903.04191 (2019) - [i33]Florian Dubost, Hieab H. Adams, Pinar Yilmaz, Gerda Bortsova, Gijs van Tulder, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks. CoRR abs/1906.01891 (2019) - [i32]Florian Dubost, Marleen de Bruijne, Marco Nardin, Adrian V. Dalca, Kathleen L. Donahue, Anne-Katrin Giese, Mark R. Etherton, Ona Wu, Marius de Groot, Wiro J. Niessen, Meike W. Vernooij, Natalia S. Rost, Markus D. Schirmer:
Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data. CoRR abs/1907.00695 (2019) - [i31]Shuai Chen, Gerda Bortsova, Antonio Garcia-Uceda Juarez, Gijs van Tulder, Marleen de Bruijne:
Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation. CoRR abs/1907.12303 (2019) - [i30]Kimberlin M. H. van Wijnen, Florian Dubost, Pinar Yilmaz, Mohammad Arfan Ikram, Wiro J. Niessen, Hieab H. Adams, Meike W. Vernooij, Marleen de Bruijne:
Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network. CoRR abs/1907.12452 (2019) - [i29]Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne:
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs. CoRR abs/1908.08588 (2019) - [i28]Chaoping Zhang, Florian Dubost, Marleen de Bruijne, Stefan Klein, Dirk H. J. Poot:
APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network. CoRR abs/1909.09006 (2019) - [i27]Florian Dubost, Benjamin Collery, Antonin Renaudier, Axel Roc, Nicolas Posocco, Gerda Bortsova, Wiro J. Niessen, Marleen de Bruijne:
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks. CoRR abs/1911.01126 (2019) - [i26]Gerda Bortsova, Florian Dubost, Laurens Hogeweg, Ioannis Katramados, Marleen de Bruijne:
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations. CoRR abs/1911.01218 (2019) - 2018
- [j33]Sepp de Raedt, Inger Mechlenburg, Maiken Stilling, Lone Rømer, Ryan J. Murphy, Mehran Armand, Jyri Lepistö, Marleen de Bruijne, Kjeld Søballe:
Reliability of computer-assisted periacetabular osteotomy using a minimally invasive approach. Int. J. Comput. Assist. Radiol. Surg. 13(12): 2021-2028 (2018) - [j32]Veronika Cheplygina, Isabel Pino Peña, Jesper Holst Pedersen, David A. Lynch, Lauge Sørensen, Marleen de Bruijne:
Transfer Learning for Multicenter Classification of Chronic Obstructive Pulmonary Disease. IEEE J. Biomed. Health Informatics 22(5): 1486-1496 (2018) - [c90]Ruwan B. Tennakoon, Amirali K. Gostar, Reza Hoseinnezhad, Marleen de Bruijne, Alireza Bab-Hadiashar:
Deep Multi-instance Volumetric Image Classification with Extreme Value Distributions. ACCV (3) 2018: 590-604 - [c89]Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Detecting emphysema with multiple instance learning. ISBI 2018: 510-513 - [c88]Silas Nyboe Ørting, Jens Petersen, Veronika Cheplygina, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Feature Learning Based on Visual Similarity Triplets in Medical Image Analysis: A Case Study of Emphysema in Chest CT Scans. CVII-STENT/LABELS@MICCAI 2018: 140-149 - [c87]A. Garcia-Uceda Juarez, Harm A. W. M. Tiddens, Marleen de Bruijne:
Automatic Airway Segmentation in Chest CT Using Convolutional Neural Networks. RAMBO+BIA+TIA@MICCAI 2018: 238-250 - [c86]Raghavendra Selvan, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction. MICCAI (2) 2018: 750-758 - [c85]Gerda Bortsova, Florian Dubost, Silas N. Ørting, Ioannis Katramados, Laurens Hogeweg, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Deep Learning from Label Proportions for Emphysema Quantification. MICCAI (2) 2018: 768-776 - [c84]Filipe Marques, Florian Dubost, Mariette Kemner-van de Corput, Harm A. W. M. Tiddens, Marleen de Bruijne:
Quantification of lung abnormalities in cystic fibrosis using deep networks. Medical Imaging: Image Processing 2018: 105741G - [c83]Zahra Sedghi Gamechi, Andrés M. Arias Lorza, Jesper Holst Pedersen, Marleen de Bruijne:
Aorta and pulmonary artery segmentation using optimal surface graph cuts in non-contrast CT. Medical Imaging: Image Processing 2018: 105742D - [i25]Florian Dubost, Hieab H. Adams, Gerda Bortsova, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI. CoRR abs/1802.05914 (2018) - [i24]Filipe Marques, Florian Dubost, Mariette Kemner-van de Corput, Harm A. W. M. Tiddens, Marleen de Bruijne:
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks. CoRR abs/1803.07991 (2018) - [i23]Raghavendra Selvan, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Mean Field Network based Graph Refinement with application to Airway Tree Extraction. CoRR abs/1804.03348 (2018) - [i22]Raghavendra Selvan, Thomas N. Kipf, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Extraction of Airways using Graph Neural Networks. CoRR abs/1804.04436 (2018) - [i21]Veronika Cheplygina, Marleen de Bruijne, Josien P. W. Pluim:
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis. CoRR abs/1804.06353 (2018) - [i20]Silas Nyboe Ørting, Jens Petersen, Veronika Cheplygina, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans. CoRR abs/1806.07131 (2018) - [i19]Raghavendra Selvan, Jens Petersen, Jesper Holst Pedersen, Marleen de Bruijne:
Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses. CoRR abs/1806.08981 (2018) - [i18]Florian Dubost, Gerda Bortsova, Hieab H. Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
Hydranet: Data Augmentation for Regression Neural Networks. CoRR abs/1807.04798 (2018) - [i17]Gerda Bortsova, Florian Dubost, Silas N. Ørting, Ioannis Katramados, Laurens Hogeweg, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Deep Learning from Label Proportions for Emphysema Quantification. CoRR abs/1807.08601 (2018) - [i16]A. Garcia-Uceda Juarez, Harm A. W. M. Tiddens, Marleen de Bruijne:
Automatic Airway Segmentation in chest CT using Convolutional Neural Networks. CoRR abs/1808.04576 (2018) - [i15]Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Learning to quantify emphysema extent: What labels do we need? CoRR abs/1810.07433 (2018) - [i14]Shuai Chen, Marleen de Bruijne:
An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images. CoRR abs/1811.03549 (2018) - [i13]Raghavendra Selvan, Thomas N. Kipf, Max Welling, Jesper Holst Pedersen, Jens Petersen, Marleen de Bruijne:
Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks. CoRR abs/1811.08674 (2018) - 2017
- [c82]Raghavendra Selvan, Jens Petersen, Jesper Holst Pedersen, Marleen de Bruijne:
Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing. GRAIL/MFCA/MICGen@MICCAI 2017: 53-63 - [c81]Silas Nyboe Ørting, Veronika Cheplygina, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Crowdsourced Emphysema Assessment. CVII-STENT/LABELS@MICCAI 2017: 126-135 - [c80]Florian Dubost, Gerda Bortsova, Hieab H. Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network. MICCAI (3) 2017: 214-221 - [c79]Gerda Bortsova, Gijs van Tulder, Florian Dubost, Tingying Peng, Nassir Navab, Aad van der Lugt, Daniel Bos, Marleen de Bruijne:
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks. MICCAI (3) 2017: 356-364 - [c78]Arna van Engelen, Marleen de Bruijne, Torben Schneider, Anouk C. van Dijk, M. Eline Kooi, Jeroen Hendrikse, Aart J. Nederveen, Wiro J. Niessen, René M. Botnar:
Evaluating Classifiers for Atherosclerotic Plaque Component Segmentation in MRI. MIUA 2017: 156-168 - [c77]Tatyana Ivanovska, Pierluigi Ciet, Adria Perez-Rovira, Anh Nguyen, Harm A. Tiddens, Liesbeth Duijts, Marleen de Bruijne, Florentin Wörgötter:
Fully Automated Lung Volume Assessment from MRI in a Population-based Child Cohort Study. VISIGRAPP (6: VISAPP) 2017: 53-58 - [i12]Veronika Cheplygina, Isabel Pino Peña, Jesper Johannes Holst Pedersen, David A. Lynch, Lauge Sørensen, Marleen de Bruijne:
Transfer learning for multi-center classification of chronic obstructive pulmonary disease. CoRR abs/1701.05013 (2017) - [i11]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Jesper Holst Pedersen, Marco Loog, Marleen de Bruijne:
Classification of COPD with Multiple Instance Learning. CoRR abs/1703.04980 (2017) - [i10]Veronika Cheplygina, Annegreet van Opbroek, Mohammad Arfan Ikram, Meike W. Vernooij, Marleen de Bruijne:
Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners. CoRR abs/1703.04981 (2017) - [i9]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Marleen de Bruijne, Marco Loog:
Label Stability in Multiple Instance Learning. CoRR abs/1703.04986 (2017) - [i8]Florian Dubost, Gerda Bortsova, Hieab H. Adams, Mohammad Arfan Ikram, Wiro J. Niessen, Meike W. Vernooij, Marleen de Bruijne:
GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network. CoRR abs/1705.07999 (2017) - [i7]Gerda Bortsova, Gijs van Tulder, Florian Dubost, Tingying Peng, Nassir Navab, Aad van der Lugt, Daniel Bos, Marleen de Bruijne:
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks. CoRR abs/1706.01148 (2017) - [i6]Isabel Pino Peña, Veronika Cheplygina, Sofia Paschaloudi, Morten Vuust, Jesper Carl, Ulla Møller Weinreich, Lasse Riis Østergaard, Marleen de Bruijne:
Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images. CoRR abs/1706.02051 (2017) - [i5]Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, Harm A. W. M. Tiddens, Marleen de Bruijne:
Early Experiences with Crowdsourcing Airway Annotations in Chest CT. CoRR abs/1706.02055 (2017) - [i4]Raghavendra Selvan, Jens Petersen, Jesper Holst Pedersen, Marleen de Bruijne:
Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing. CoRR abs/1708.02096 (2017) - 2016
- [j31]Marleen de Bruijne:
Machine learning approaches in medical image analysis: From detection to diagnosis. Medical Image Anal. 33: 94-97 (2016) - [j30]Andrés M. Arias Lorza, Jens Petersen, Arna van Engelen, Mariana Selwaness, Aad van der Lugt, Wiro J. Niessen, Marleen de Bruijne:
Carotid Artery Wall Segmentation in Multispectral MRI by Coupled Optimal Surface Graph Cuts. IEEE Trans. Medical Imaging 35(3): 901-911 (2016) - [j29]Gijs van Tulder, Marleen de Bruijne:
Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines. IEEE Trans. Medical Imaging 35(5): 1262-1272 (2016) - [c76]Veronika Cheplygina, Annegreet van Opbroek, Mohammad Arfan Ikram, Meike W. Vernooij, Marleen de Bruijne:
Asymmetric similarity-weighted ensembles for image segmentation. ISBI 2016: 273-277 - [c75]Gijs van Tulder, Marleen de Bruijne:
Representation Learning for Cross-Modality Classification. MCV/BAMBI@MICCAI 2016: 126-136 - [c74]Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, Harm A. W. M. Tiddens, Marleen de Bruijne:
Early Experiences with Crowdsourcing Airway Annotations in Chest CT. LABELS/DLMIA@MICCAI 2016: 209-218 - [i3]Raghavendra Selvan, Jens Petersen, Jesper Johannes Holst Pedersen, Marleen de Bruijne:
Extraction of airway trees using multiple hypothesis tracking and template matching. CoRR abs/1611.08131 (2016) - 2015
- [j28]Adriënne M. Mendrik, Koen L. Vincken, Hugo J. Kuijf, Marcel Breeuwer, Willem H. Bouvy, Jeroen de Bresser, Amir Alansary, Marleen de Bruijne, Aaron Carass, Ayman El-Baz, Amod Jog, Ranveer Katyal, Ali R. Khan, Fedde van der Lijn, Qaiser Mahmood, Ryan Mukherjee, Annegreet van Opbroek, Sahil Paneri, Sérgio Pereira, Mikael Persson, Martin Rajchl, Duygu Sarikaya, Örjan Smedby, Carlos A. Silva, Henri A. Vrooman, Saurabh Vyas, Chunliang Wang, Liang Zhao, Geert Jan Biessels, Max A. Viergever:
MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans. Comput. Intell. Neurosci. 2015: 813696:1-813696:16 (2015) - [j27]Annegreet van Opbroek, Meike W. Vernooij, Mohammad Arfan Ikram, Marleen de Bruijne:
Weighting training images by maximizing distribution similarity for supervised segmentation across scanners. Medical Image Anal. 24(1): 245-254 (2015) - [j26]Annegreet van Opbroek, Mohammad Arfan Ikram, Meike W. Vernooij, Marleen de Bruijne:
Transfer Learning Improves Supervised Image Segmentation Across Imaging Protocols. IEEE Trans. Medical Imaging 34(5): 1018-1030 (2015) - [j25]Aasa Feragen, Jens Petersen, Megan Owen, Pechin Lo, Laura Hohwu Thomsen, Mathilde Marie Winkler Wille, Asger Dirksen, Marleen de Bruijne:
Geodesic Atlas-Based Labeling of Anatomical Trees: Application and Evaluation on Airways Extracted From CT. IEEE Trans. Medical Imaging 34(6): 1212-1226 (2015) - [j24]Arna van Engelen, Anouk C. van Dijk, Martine T. B. Truijman, Ronald van't Klooster, Annegreet van Opbroek, Aad van der Lugt, Wiro J. Niessen, M. Eline Kooi, Marleen de Bruijne:
Multi-Center MRI Carotid Plaque Component Segmentation Using Feature Normalization and Transfer Learning. IEEE Trans. Medical Imaging 34(6): 1294-1305 (2015) - [c73]Annegreet van Opbroek, Hakim C. Achterberg, Marleen de Bruijne:
Feature-Space Transformation Improves Supervised Segmentation Across Scanners. MLMMI@ICML 2015: 85-93 - [c72]Gijs van Tulder, Marleen de Bruijne:
Why Does Synthesized Data Improve Multi-sequence Classification? MICCAI (1) 2015: 531-538 - [c71]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Marleen de Bruijne, Marco Loog:
Label Stability in Multiple Instance Learning. MICCAI (1) 2015: 539-546 - 2014
- [j23]Jens Petersen, Mads Nielsen, Pechin Lo, Lars Haug Nordenmark, Jesper Johannes Holst Pedersen, Mathilde Marie Winkler Wille, Asger Dirksen, Marleen de Bruijne:
Optimal surface segmentation using flow lines to quantify airway abnormalities in chronic obstructive pulmonary disease. Medical Image Anal. 18(3): 531-541 (2014) - [j22]Ruwan B. Tennakoon, Alireza Bab-Hadiashar, Zhenwei Cao, Marleen de Bruijne:
Nonrigid Registration of Volumetric Images Using Ranked Order Statistics. IEEE Trans. Medical Imaging 33(2): 422-432 (2014) - [c70]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Jesper Johannes Holst Pedersen, Marco Loog, Marleen de Bruijne:
Classification of COPD with Multiple Instance Learning. ICPR 2014: 1508-1513 - [c69]Gijs van Tulder, Marleen de Bruijne:
Learning Features for Tissue Classification with the Classification Restricted Boltzmann Machine. MCV 2014: 47-58 - 2013
- [j21]Nora Baka, Coert Metz, Carl J. Schultz, Lisan Neefjes, Robert Jan van Geuns, Boudewijn P. F. Lelieveldt, Wiro J. Niessen, Theo van Walsum, Marleen de Bruijne:
Statistical coronary motion models for 2D + t/3D registration of X-ray coronary angiography and CTA. Medical Image Anal. 17(6): 698-709 (2013) - [j20]Aasa Feragen, Pechin Lo, Marleen de Bruijne, Mads Nielsen, François Lauze:
Toward a Theory of Statistical Tree-Shape Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 2008-2021 (2013) - [j19]Alireza Bab-Hadiashar, Ruwan B. Tennakoon, Marleen de Bruijne:
Quantification of Smoothing Requirement for 3D Optic Flow Calculation of Volumetric Images. IEEE Trans. Image Process. 22(6): 2128-2137 (2013) - [c68]Aasa Feragen, Megan Owen, Jens Petersen, Mathilde M. W. Wille, Laura H. Thomsen, Asger Dirksen, Marleen de Bruijne:
Tree-Space Statistics and Approximations for Large-Scale Analysis of Anatomical Trees. IPMI 2013: 74-85 - [c67]Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Johannes Holst Pedersen, Karsten M. Borgwardt, Marleen de Bruijne:
Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry. IPMI 2013: 171-183 - [c66]Ruwan Bandara Tennakoon, Alireza Bab-Hadiashar, Marleen de Bruijne, Zhenwei Cao:
Efficient nonrigid registration using ranked order statistics. ISBI 2013: 496-499 - [c65]