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2020 – today
- 2024
[j18]Marc Aubreville
, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonas Ammeling, Jonathan Ganz, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Çayir, Hongyan Gu, Xiang Anthony Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen Yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram:
Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. Medical Image Anal. 94: 103155 (2024)- [j17]Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Shenghua Cheng, Jiabo Ma, John Pocock, Josien P. W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan-E-Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Xiuli Liu, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi:
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. IEEE J. Biomed. Health Informatics 28(3): 1161-1172 (2024) - [c21]Marc Aubreville, Frauke Wilm, Nikolas Stathonikos, Katharina Breininger, Taryn A. Donovan, Samir Jabari, Robert Klopfleisch, Mitko Veta, Jonathan Ganz, Jonas Ammeling, Paul J. van Diest, Christof A. Bertram:
Abstract: Comprehensive Multi-domain Dataset for Mitotic Figure Detection. Bildverarbeitung für die Medizin 2024: 136 - [i32]Ruben T. Lucassen, Willeke A. M. Blokx, Mitko Veta:
Tissue Cross-Section and Pen Marking Segmentation in Whole Slide Images. CoRR abs/2401.13511 (2024) - [i31]Hassan Keshvarikhojasteh, Josien P. W. Pluim, Mitko Veta:
Multiple Instance Learning with random sampling for Whole Slide Image Classification. CoRR abs/2403.05351 (2024) - [i30]Hong Liu, Haosen Yang, Paul J. van Diest, Josien P. W. Pluim, Mitko Veta:
WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide images. CoRR abs/2403.09257 (2024) - [i29]Hassan Keshvarikhojasteh, Josien P. W. Pluim, Mitko Veta:
Multi-head Attention-based Deep Multiple Instance Learning. CoRR abs/2404.05362 (2024) - 2023
- [j16]Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas K. Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Adam Shephard, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, Yubo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen Yang, Xiyue Wang, Ramona Erber, Andrea Klang, Karoline Lipnik, Pompei Bolfa, Michael J. Dark, Gabriel Wasinger, Mitko Veta, Katharina Breininger:
Mitosis domain generalization in histopathology images - The MIDOG challenge. Medical Image Anal. 84: 102699 (2023) - [j15]Ruben T. Lucassen, Mohammad H. Jafari, Nicole M. Duggan, Nick Jowkar, Alireza Mehrtash, Chanel E. Fischetti, Denie Bernier, Kira Prentice, Erik P. Duhaime, Mike Jin, Purang Abolmaesumi, Friso G. Heslinga, Mitko Veta, Maria Alejandra Duran Mendicuti, Sarah F. Frisken, Paul B. Shyn, Alexandra J. Golby, Edward W. Boyer, William M. Wells III, Andrew J. Goldsmith, Tina Kapur:
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound. IEEE J. Biomed. Health Informatics 27(9): 4352-4361 (2023) - [c20]Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas K. Maier, Mitko Veta, Katharina Breininger:
Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images. Bildverarbeitung für die Medizin 2023: 115 - [i28]Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Jiabo Ma, Jiamei Sun, Johnathon Pocock, Josien P. W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan E Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Thomas Watson, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi:
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. CoRR abs/2301.06304 (2023) - [i27]Julian P. Merkofer, Dennis M. J. van de Sande, Sina Amirrajab, Gerhard S. Drenthen, Mitko Veta, Jacobus F. A. Jansen, Marcel Breeuwer, Ruud J. G. van Sloun:
A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge. CoRR abs/2306.02984 (2023) - [i26]Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonathan Ganz, Jonas Ammeling, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Cayir, Hongyan Gu, Xiang 'Anthony' Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen Yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram:
Domain generalization across tumor types, laboratories, and species - insights from the 2022 edition of the Mitosis Domain Generalization Challenge. CoRR abs/2309.15589 (2023) - 2022
- [j14]Didier R. P. R. M. Lustermans, Sina Amirrajab, Mitko Veta, Marcel Breeuwer, Cian M. Scannell:
Optimized automated cardiac MR scar quantification with GAN-based data augmentation. Comput. Methods Programs Biomed. 226: 107116 (2022) - [j13]Rudolf L. M. van Herten, Amedeo Chiribiri, Marcel Breeuwer, Mitko Veta, Cian M. Scannell:
Physics-informed neural networks for myocardial perfusion MRI quantification. Medical Image Anal. 78: 102399 (2022) - [i25]Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie D. ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas K. Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Nasir M. Rajpoot, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, Yubo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen Yang, Xiyue Wang, Mitko Veta, Katharina Breininger:
Mitosis domain generalization in histopathology images - The MIDOG challenge. CoRR abs/2204.03742 (2022) - 2021
- [j12]Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta:
Roto-translation equivariant convolutional networks: Application to histopathology image analysis. Medical Image Anal. 68: 101849 (2021) - [j11]Gerda Bortsova, Cristina González-Gonzalo, Suzanne C. Wetstein, Florian Dubost, Ioannis Katramados, Laurens Hogeweg, Bart Liefers, Bram van Ginneken, Josien P. W. Pluim, Mitko Veta, Clara I. Sánchez, Marleen de Bruijne:
Adversarial attack vulnerability of medical image analysis systems: Unexplored factors. Medical Image Anal. 73: 102141 (2021) - [j10]Coen de Vente, Pieter Vos, Matin Hosseinzadeh, Josien P. W. Pluim, Mitko Veta:
Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI. IEEE Trans. Biomed. Eng. 68(2): 374-383 (2021) - [j9]Linde S. Hesse, Grey Kuling, Mitko Veta, Anne L. Martel:
Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols. IEEE Trans. Biomed. Eng. 68(3): 759-770 (2021) - [j8]Francesco Ciompi, Mitko Veta, Jeroen van der Laak, Nasir M. Rajpoot:
Editorial Computational Pathology. IEEE J. Biomed. Health Informatics 25(2): 303-306 (2021) - [j7]Víctor M. Campello, Polyxeni Gkontra, Cristian Izquierdo, Carlos Martín-Isla, Alireza Sojoudi, Peter M. Full, Klaus H. Maier-Hein, Yao Zhang, Zhiqiang He, Jun Ma, Mario Parreño, Alberto Albiol, Fanwei Kong, Shawn C. Shadden, Jorge Corral Acero, Vaanathi Sundaresan, Mina Saber, Mustafa A. Alattar, Hongwei Li, Bjoern H. Menze, Firas Khader, Christoph Haarburger, Cian M. Scannell, Mitko Veta, Adam Carscadden, Kumaradevan Punithakumar, Xiao Liu, Sotirios A. Tsaftaris, Xiaoqiong Huang, Xin Yang, Lei Li, Xiahai Zhuang, David Viladés, Martín Luís Descalzo, Andrea Guala, Lucia La Mura, Matthias G. W. Friedrich, Ria Garg, Julie Lebel, Filipe Henriques, Mahir Karakas, Ersin Çavus, Steffen E. Petersen, Sergio Escalera, Santi Seguí, José F. Rodríguez Palomares, Karim Lekadir:
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge. IEEE Trans. Medical Imaging 40(12): 3543-3554 (2021) - [c19]Bram M. van der Velden, Mitko Veta, Josien P. W. Pluim, Mark Alberti, Friso G. Heslinga:
Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans. OMIA@MICCAI 2021: 72-81 - [e3]Manfredo Atzori, Nikolay Burlutskiy, Francesco Ciompi, Zhang Li, Fayyaz A. Minhas, Henning Müller, Tingying Peng, Nasir M. Rajpoot, Ben Torben-Nielsen, Jeroen van der Laak, Mitko Veta, Yinyin Yuan, Inti Zlobec:
MICCAI Workshop on Computational Pathology, COMPAY@MICCAI 2021, 27 September 2021, Virtual Event. Proceedings of Machine Learning Research 156, PMLR 2021 [contents] - [i24]Friso G. Heslinga, Ruben T. Lucassen, Myrthe A. van den Berg, Luuk van der Hoek, Josien P. W. Pluim, Javier Cabrerizo, Mark Alberti, Mitko Veta:
Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty. CoRR abs/2102.07846 (2021) - [i23]Marc Aubreville, Christof Bertram, Mitko Veta, Robert Klopfleisch, Nikolas Stathonikos, Katharina Breininger, Natalie D. ter Hoeve, Francesco Ciompi, Andreas Maier:
Quantifying the Scanner-Induced Domain Gap in Mitosis Detection. CoRR abs/2103.16515 (2021) - [i22]Didier R. P. R. M. Lustermans, Sina Amirrajab, Mitko Veta, Marcel Breeuwer, Cian M. Scannell:
Optimized Automated Cardiac MR Scar Quantification with GAN-Based Data Augmentation. CoRR abs/2109.12940 (2021) - 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) - [c18]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 - [c17]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. Medical Imaging: Computer-Aided Diagnosis 2020 - [c16]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 - [c15]Cian M. Scannell, Amedeo Chiribiri, Mitko Veta:
Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation. M&Ms and EMIDEC/STACOM@MICCAI 2020: 228-237 - [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, Xinjian 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, Faik 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, Faik 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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