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2020 – today
- 2020
[j6]Koen A. J. Eppenhof
, Maxime W. Lafarge, Mitko Veta, Josien P. W. Pluim:
Progressively Trained Convolutional Neural Networks for Deformable Image Registration. IEEE Trans. Medical Imaging 39(5): 1594-1604 (2020)- [c16]Mike van Zon, Nikolas Stathonikos, Willeke A. M. Blokx, Selim Komina, Sybren L. N. Maas, Josien P. W. Pluim, Paul J. van Diest, Mitko Veta:
Segmentation and Classification of Melanoma and Nevus in Whole Slide Images. ISBI 2020: 263-266 - [c15]Christof A. Bertram, Mitko Veta, Christian Marzahl, Nikolas Stathonikos, Andreas K. Maier, Robert Klopfleisch, Marc Aubreville:
Are Pathologist-Defined Labels Reproducible? Comparison of the TUPAC16 Mitotic Figure Dataset with an Alternative Set of Labels. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 204-213 - [i21]Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta:
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis. CoRR abs/2002.08725 (2020) - [i20]Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra, Alessandro Masci, Cristiana Corsi, Coen de Vente, Mitko Veta, Rashed Karim, Chandrakanth Jayachandran Preetha, Sandy Engelhardt, Mengyun Qiao, Yuanyuan Wang, Qian Tao, Marta Nuñez Garcia, Oscar Camara, Nicoló Savioli, Pablo Lamata, Jichao Zhao:
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging. CoRR abs/2004.12314 (2020) - [i19]Friso G. Heslinga, Mark Alberti, Josien P. W. Pluim, Javier Cabrerizo, Mitko Veta:
Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks. CoRR abs/2004.12807 (2020) - [i18]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) - [i17]Christof A. Bertram, Mitko Veta, Christian Marzahl, Nikolas Stathonikos, Andreas K. Maier, Robert Klopfleisch, Marc Aubreville:
Are pathologist-defined labels reproducible? Comparison of the TUPAC16 mitotic figure dataset with an alternative set of labels. CoRR abs/2007.05351 (2020) - [i16]Maxime W. Lafarge, Josien P. W. Pluim, Mitko Veta:
Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology. CoRR abs/2008.11673 (2020) - [i15]Cian M. Scannell, Amedeo Chiribiri, Mitko Veta:
Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation. CoRR abs/2008.11776 (2020) - [i14]Suzanne C. Wetstein, Nikolas Stathonikos, Josien P. W. Pluim, Yujing J. Heng, Natalie D. ter Hoeve, Celien P. H. Vreuls, Paul J. van Diest, Mitko Veta:
Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images. CoRR abs/2010.03244 (2020) - [i13]Rudolf L. M. van Herten, Amedeo Chiribiri, Marcel Breeuwer, Mitko Veta, Cian M. Scannell:
Physics-informed neural networks for myocardial perfusion MRI quantification. CoRR abs/2011.12844 (2020)
2010 – 2019
- 2019
- [j5]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. Medical Image Anal. 54: 111-121 (2019) - [j4]Mitko Veta:
Corrigendum to "Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge" [Medical Image Analysis, 54 (2019) 111-121]. Medical Image Anal. 56: 43 (2019) - [c14]Maxime W. Lafarge, Juan C. Caicedo, Anne E. Carpenter, Josien P. W. Pluim, Shantanu Singh, Mitko Veta:
Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. MIDL 2019: 315-325 - [c13]Suzanne C. Wetstein, Allison M. Onken, Gabrielle M. Baker, Michael E. Pyle, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, Mitko Veta:
Detection of acini in histopathology slides: towards automated prediction of breast cancer risk. Medical Imaging: Digital Pathology 2019: 109560Q - [c12]Friso G. Heslinga, Josien P. W. Pluim, Behdad Dashtbozorg, Tos T. J. M. Berendschot, A. J. H. M. Houben, Ronald M. A. Henry, Mitko Veta:
Approximation of a pipeline of unsupervised retina image analysis methods with a CNN. Medical Imaging: Image Processing 2019: 109491N - [c11]Mike van Zon, Mitko Veta, Shuo Li:
Automatic cardiac landmark localization by a recurrent neural network. Medical Imaging: Image Processing 2019: 1094916 - [p1]Dragan Bosnacki, Natal A. W. van Riel, Mitko Veta:
Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis. Automated Reasoning for Systems Biology and Medicine 2019: 453-469 - [e2]Constantino Carlos Reyes-Aldasoro, Andrew Janowczyk, Mitko Veta, Peter Bankhead, Korsuk Sirinukunwattana:
Digital Pathology - 15th European Congress, ECDP 2019, Warwick, UK, April 10-13, 2019, Proceedings. Lecture Notes in Computer Science 11435, Springer 2019, ISBN 978-3-030-23936-7 [contents] - [i12]Cian M. Scannell, Piet van den Bosch, Amedeo Chiribiri, Jack Lee, Marcel Breeuwer, Mitko Veta:
Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI. CoRR abs/1907.11899 (2019) - [i11]Linde S. Hesse, Grey Kuling, Mitko Veta, Anne L. Martel:
Intensity augmentation for domain transfer of whole breast segmentation in MRI. CoRR abs/1909.02642 (2019) - [i10]Suzanne C. Wetstein, Allison M. Onken, Christina Luffman, Gabrielle M. Baker, Michael E. Pyle, Kevin H. Kensler, Ying Liu, Bart Bakker, Ruud Vlutters, Marinus B. van Leeuwen, Laura C. Collins, Stuart J. Schnitt, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, Mitko Veta:
Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk. CoRR abs/1911.00036 (2019) - [i9]Friso G. Heslinga, Josien P. W. Pluim, A. J. H. M. Houben, Miranda T. Schram, Ronald M. A. Henry, Coen D. A. Stehouwer, Marleen J. van Greevenbroek, Tos T. J. M. Berendschot, Mitko Veta:
Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study. CoRR abs/1911.10022 (2019) - 2018
- [c10]Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta:
Inferring a third spatial dimension from 2D histological images. ISBI 2018: 586-589 - [c9]Coen de Vente, Mitko Veta, Orod Razeghi, Steven A. Niederer, Josien P. W. Pluim, Kawal S. Rhode, Rashed Karim:
Convolutional Neural Networks for Segmentation of the Left Atrium from Gadolinium-Enhancement MRI Images. STACOM@MICCAI 2018: 348-356 - [c8]Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits:
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. MICCAI (1) 2018: 440-448 - [c7]Koen A. J. Eppenhof, Maxime W. Lafarge, Pim Moeskops, Mitko Veta, Josien P. W. Pluim:
Deformable image registration using convolutional neural networks. Medical Imaging: Image Processing 2018: 105740S - [e1]Danail Stoyanov, Zeike Taylor, Francesco Ciompi, Yanwu Xu, Anne L. Martel, Lena Maier-Hein, Nasir M. Rajpoot, Jeroen van der Laak, Mitko Veta, Stephen J. McKenna, David R. J. Snead, Emanuele Trucco, Mona Kathryn Garvin, Xin Jan Chen, Hrvoje Bogunovic:
Computational Pathology and Ophthalmic Medical Image Analysis - First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings. Lecture Notes in Computer Science 11039, Springer 2018, ISBN 978-3-030-00948-9 [contents] - [i8]Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta:
Inferring a Third Spatial Dimension from 2D Histological Images. CoRR abs/1801.03431 (2018) - [i7]Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits:
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. CoRR abs/1804.03393 (2018) - [i6]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir M. Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. CoRR abs/1807.08284 (2018) - 2017
- [c6]Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim:
Adversarial Training and Dilated Convolutions for Brain MRI Segmentation. DLMIA/ML-CDS@MICCAI 2017: 56-64 - [c5]Veronika Cheplygina, Pim Moeskops, Mitko Veta, Behdad Dashtbozorg, Josien P. W. Pluim:
Exploring the Similarity of Medical Imaging Classification Problems. CVII-STENT/LABELS@MICCAI 2017: 59-66 - [c4]Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta:
Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images. DLMIA/ML-CDS@MICCAI 2017: 83-91 - [i5]Veronika Cheplygina, Pim Moeskops, Mitko Veta, Behdad Dasht Bozorg, Josien P. W. Pluim:
Exploring the similarity of medical imaging classification problems. CoRR abs/1706.03509 (2017) - [i4]Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim:
Adversarial training and dilated convolutions for brain MRI segmentation. CoRR abs/1707.03195 (2017) - [i3]Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta:
Domain-adversarial neural networks to address the appearance variability of histopathology images. CoRR abs/1707.06183 (2017) - 2016
- [c3]Mitko Veta, Paul J. van Diest, Josien P. W. Pluim:
Cutting Out the Middleman: Measuring Nuclear Area in Histopathology Slides Without Segmentation. MICCAI (2) 2016: 632-639 - [i2]Mitko Veta, Paul J. van Diest, Josien P. W. Pluim:
Cutting out the middleman: measuring nuclear area in histopathology slides without segmentation. CoRR abs/1606.06127 (2016) - 2015
- [j3]Mitko Veta, Paul J. van Diest, Stefan M. Willems, Haibo Wang, Anant Madabhushi, Angel Cruz-Roa, Fabio A. González, Anders Boesen Lindbo Larsen, Jacob S. Vestergaard, Anders B. Dahl, Dan C. Ciresan, Jürgen Schmidhuber, Alessandro Giusti, Luca Maria Gambardella, F. Boray Tek, Thomas Walter, Ching-Wei Wang, Satoshi Kondo, Bogdan J. Matuszewski, Frédéric Precioso, Violet Snell, Josef Kittler, Teófilo Emídio de Campos, Adnan Mujahid Khan, Nasir M. Rajpoot, Evdokia Arkoumani, Miangela M. Lacle, Max A. Viergever, Josien P. W. Pluim:
Assessment of algorithms for mitosis detection in breast cancer histopathology images. Medical Image Anal. 20(1): 237-248 (2015) - 2014
- [j2]Mitko Veta, Josien P. W. Pluim, Paul J. van Diest, Max A. Viergever:
Breast Cancer Histopathology Image Analysis: A Review. IEEE Trans. Biomed. Eng. 61(5): 1400-1411 (2014) - [j1]Mitko Veta, Josien P. W. Pluim, Paul J. van Diest, Max A. Viergever:
Corrections to "Breast Cancer Histopathology Image Analysis: A Review". IEEE Trans. Biomed. Eng. 61(11): 2819 (2014) - [i1]Mitko Veta, Paul J. van Diest, Stefan M. Willems, Haibo Wang, Anant Madabhushi, Angel Cruz-Roa, Fabio A. González, Anders Boesen Lindbo Larsen, Jacob S. Vestergaard, Anders B. Dahl, Dan C. Ciresan, Jürgen Schmidhuber, Alessandro Giusti, Luca Maria Gambardella, F. Boray Tek, Thomas Walter, Ching-Wei Wang, Satoshi Kondo, Bogdan J. Matuszewski, Frédéric Precioso, Violet Snell, Josef Kittler, Teófilo Emídio de Campos, Adnan Mujahid Khan, Nasir M. Rajpoot, Evdokia Arkoumani, Miangela M. Lacle, Max A. Viergever, Josien P. W. Pluim:
Assessment of algorithms for mitosis detection in breast cancer histopathology images. CoRR abs/1411.5825 (2014) - 2013
- [c2]Mitko Veta, Paul J. van Diest, Josien P. W. Pluim:
Detecting mitotic figures in breast cancer histopathology images. Medical Imaging: Digital Pathology 2013: 867607 - 2011
- [c1]Mitko Veta, A. Huisman, Max A. Viergever, Paul J. van Diest, Josien P. W. Pluim:
Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images. ISBI 2011: 618-621
Coauthor Index
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