Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images. - Mitko Veta; A. Huisman; Max A. Viergever; Paul J. van Diest; Josien P. W. Pluim (ISBI, 2011)

Detecting mitotic figures in breast cancer histopathology images. - Mitko Veta; Paul J. van Diest; Josien P. W. Pluim (Digital Pathology, 2013)

Breast Cancer Histopathology Image Analysis: A Review. - Mitko Veta; Josien P. W. Pluim; Paul J. van Diest; Max A. Viergever (IEEE Trans. Biomed. Eng., 2014)

Corrections to "Breast Cancer Histopathology Image Analysis: A Review". - Mitko Veta; Josien P. W. Pluim; Paul J. van Diest; Max A. Viergever (IEEE Trans. Biomed. Eng., 2014)

Assessment of algorithms for mitosis detection in breast cancer histopathology images. - Mitko Veta; Paul J. van Diest; Stefan M. Willems; Haibo Wang; Anant Madabhushi; Angel Cruz-Roa; Fabio A. González 001; Anders Boesen Lindbo Larsen; Jacob S. Vestergaard; Anders B. Dahl; Dan C. Ciresan; Jürgen Schmidhuber; et al. (Medical Image Anal., 2015)

Cutting Out the Middleman: Measuring Nuclear Area in Histopathology Slides Without Segmentation. - Mitko Veta; Paul J. van Diest; Josien P. W. Pluim (MICCAI (2), 2016)

Exploring the Similarity of Medical Imaging Classification Problems. - Veronika Cheplygina; Pim Moeskops; Mitko Veta; Behdad Dashtbozorg; Josien P. W. Pluim (CVII-STENT/LABELS@MICCAI, 2017)

Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images. - Maxime W. Lafarge; Josien P. W. Pluim; Koen A. J. Eppenhof; Pim Moeskops; Mitko Veta (DLMIA/ML-CDS@MICCAI, 2017)

Adversarial Training and Dilated Convolutions for Brain MRI Segmentation. - Pim Moeskops; Mitko Veta; Maxime W. Lafarge; Koen A. J. Eppenhof; Josien P. W. Pluim (DLMIA/ML-CDS@MICCAI, 2017)

Inferring a third spatial dimension from 2D histological images. - Maxime W. Lafarge; Josien P. W. Pluim; Koen A. J. Eppenhof; Pim Moeskops; Mitko Veta (ISBI, 2018)

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. - Erik J. Bekkers; Maxime W. Lafarge; Mitko Veta; Koen A. J. Eppenhof; Josien P. W. Pluim; Remco Duits (MICCAI (1), 2018)

Convolutional Neural Networks for Segmentation of the Left Atrium from Gadolinium-Enhancement MRI Images. - Coen de Vente; Mitko Veta; Orod Razeghi; Steven A. Niederer; Josien P. W. Pluim; Kawal S. Rhode; Rashed Karim (STACOM@MICCAI, 2018)

Deformable image registration using convolutional neural networks. - Koen A. J. Eppenhof; Maxime W. Lafarge; Pim Moeskops; Mitko Veta; Josien P. W. Pluim (Image Processing, 2018)

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. - 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; et al. (CoRR, 2018)

Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. - Maxime W. Lafarge; Juan C. Caicedo; Anne E. Carpenter; Josien P. W. Pluim; Shantanu Singh; Mitko Veta (MIDL, 2019)

Detection of acini in histopathology slides: towards automated prediction of breast cancer risk. - Suzanne C. Wetstein; Allison M. Onken; Gabrielle M. Baker; Michael E. Pyle; Josien P. W. Pluim; Rulla M. Tamimi; Yujing J. Heng; Mitko Veta (Digital Pathology, 2019)

Approximation of a pipeline of unsupervised retina image analysis methods with a CNN. - 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 (Image Processing, 2019)

Automatic cardiac landmark localization by a recurrent neural network. - Mike van Zon; Mitko Veta; Shuo Li 001 (Image Processing, 2019)

Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI. - Cian M. Scannell; Piet van den Bosch; Amedeo Chiribiri; Jack Lee; Marcel Breeuwer; Mitko Veta (CoRR, 2019)

Intensity augmentation for domain transfer of whole breast segmentation in MRI. - Linde S. Hesse; Grey Kuling; Mitko Veta; Anne L. Martel (CoRR, 2019)

Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk. - 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; et al. (CoRR, 2019)

Corrigendum to "Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge" [Medical Image Analysis, 54 (2019) 111-121]. - Mitko Veta (Medical Image Anal., 2019)

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. - 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; et al. (Medical Image Anal., 2019)

Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis. - Dragan Bosnacki; Natal A. W. van Riel; Mitko Veta (Automated Reasoning for Systems Biology and Medicine, 2019)

Segmentation and Classification of Melanoma and Nevus in Whole Slide Images. - 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 (ISBI, 2020)

Direct classification of type 2 diabetes from retinal fundus images in a population-based sample from the Maastricht study. - 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 (Computer-Aided Diagnosis, 2020)

Are Pathologist-Defined Labels Reproducible? Comparison of the TUPAC16 Mitotic Figure Dataset with an Alternative Set of Labels. - Christof A. Bertram; Mitko Veta; Christian Marzahl; Nikolas Stathonikos; Andreas K. Maier; Robert Klopfleisch; Marc Aubreville (iMIMIC/MIL3ID/LABELS@MICCAI, 2020)

Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation. - Cian M. Scannell; Amedeo Chiribiri; Mitko Veta (M&Ms and EMIDEC/STACOM@MICCAI, 2020)

A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging. - Zhaohan Xiong; Qing Xia 002; Zhiqiang Hu; Ning Huang; Cheng Bian; Yefeng Zheng 001; Sulaiman Vesal; Nishant Ravikumar; Andreas K. Maier; Xin Yang 009; Pheng-Ann Heng; Dong Ni 001; et al. (CoRR, 2020)

Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks. - Friso G. Heslinga; Mark Alberti; Josien P. W. Pluim; Javier Cabrerizo; Mitko Veta (CoRR, 2020)

Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology. - Maxime W. Lafarge; Josien P. W. Pluim; Mitko Veta (CoRR, 2020)

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images. - 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 (CoRR, 2020)

Progressively Trained Convolutional Neural Networks for Deformable Image Registration. - Koen A. J. Eppenhof; Maxime W. Lafarge; Mitko Veta; Josien P. W. Pluim (IEEE Trans. Medical Imaging, 2020)

Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans. - Bram M. van der Velden; Mitko Veta; Josien P. W. Pluim; Mark Alberti; Friso G. Heslinga (OMIA@MICCAI, 2021)

Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty. - 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 (CoRR, 2021)

Quantifying the Scanner-Induced Domain Gap in Mitosis Detection. - Marc Aubreville; Christof Bertram; Mitko Veta; Robert Klopfleisch; Nikolas Stathonikos; Katharina Breininger; Natalie D. ter Hoeve; Francesco Ciompi; Andreas Maier 001 (CoRR, 2021)

Adversarial attack vulnerability of medical image analysis systems: Unexplored factors. - 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 (Medical Image Anal., 2021)

Roto-translation equivariant convolutional networks: Application to histopathology image analysis. - Maxime W. Lafarge; Erik J. Bekkers; Josien P. W. Pluim; Remco Duits; Mitko Veta (Medical Image Anal., 2021)

Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols. - Linde S. Hesse; Grey Kuling; Mitko Veta; Anne L. Martel (IEEE Trans. Biomed. Eng., 2021)

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI. - Coen de Vente; Pieter Vos; Matin Hosseinzadeh; Josien P. W. Pluim; Mitko Veta (IEEE Trans. Biomed. Eng., 2021)

Editorial Computational Pathology. - Francesco Ciompi; Mitko Veta; Jeroen van der Laak; Nasir M. Rajpoot (IEEE J. Biomed. Health Informatics, 2021)

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge. - Víctor M. Campello; Polyxeni Gkontra; Cristian Izquierdo; Carlos Martín-Isla; Alireza Sojoudi; Peter M. Full; Klaus H. Maier-Hein; Yao Zhang 010; Zhiqiang He 002; Jun Ma 016; Mario Parreño; Alberto Albiol; et al. (IEEE Trans. Medical Imaging, 2021)

Optimized automated cardiac MR scar quantification with GAN-based data augmentation. - Didier R. P. R. M. Lustermans; Sina Amirrajab; Mitko Veta; Marcel Breeuwer; Cian M. Scannell (Comput. Methods Programs Biomed., 2022)

Mitosis domain generalization in histopathology images - The MIDOG challenge. - 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; et al. (CoRR, 2022)

Physics-informed neural networks for myocardial perfusion MRI quantification. - Rudolf L. M. van Herten; Amedeo Chiribiri; Marcel Breeuwer; Mitko Veta; Cian M. Scannell (Medical Image Anal., 2022)

Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images. - 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; Mitko Veta; Katharina Breininger (Bildverarbeitung für die Medizin, 2023)

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. - 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; et al. (CoRR, 2023)

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge. - 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 (CoRR, 2023)

Mitosis domain generalization in histopathology images - The MIDOG challenge. - 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; et al. (Medical Image Anal., 2023)

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound. - Ruben T. Lucassen; Mohammad H. Jafari 001; Nicole M. Duggan; Nick Jowkar; Alireza Mehrtash; Chanel E. Fischetti; Denie Bernier; Kira Prentice; Erik P. Duhaime; Mike Jin; Purang Abolmaesumi; Friso G. Heslinga; et al. (IEEE J. Biomed. Health Informatics, 2023)

Abstract: Comprehensive Multi-domain Dataset for Mitotic Figure Detection. - 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 (Bildverarbeitung für die Medizin, 2024)

Multi-head Attention-based Deep Multiple Instance Learning. - Hassan Keshvarikhojasteh; Josien P. W. Pluim; Mitko Veta (COMPAY@MICCAI, 2024)

WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide images. - Hong Liu; Haosen Yang 003; Paul J. van Diest; Josien P. W. Pluim; Mitko Veta (COMPAY@MICCAI, 2024)

Preprocessing Pathology Reports for Vision-Language Model Development. - Ruben T. Lucassen; Tijn van de Luijtgaarden; Sander P. J. Moonemans; Willeke A. M. Blokx; Mitko Veta (COMPAY@MICCAI, 2024)

Tissue Cross-Section and Pen Marking Segmentation in Whole Slide Images. - Ruben T. Lucassen; Willeke A. M. Blokx; Mitko Veta (CoRR, 2024)

Multiple Instance Learning with random sampling for Whole Slide Image Classification. - Hassan Keshvarikhojasteh; Josien P. W. Pluim; Mitko Veta (CoRR, 2024)

Artificial Intelligence-Based Triaging of Cutaneous Melanocytic Lesions. - Ruben T. Lucassen; Nikolas Stathonikos; Gerben E. Breimer; Mitko Veta; Willeke A. M. Blokx (CoRR, 2024)

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. - 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; et al. (Medical Image Anal., 2024)

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. - 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; et al. (IEEE J. Biomed. Health Informatics, 2024)

On the Importance of Text Preprocessing for Multimodal Representation Learning and Pathology Report Generation. - Ruben T. Lucassen; Tijn van de Luijtgaarden; Sander P. J. Moonemans; Gerben E. Breimer; Willeke A. M. Blokx; Mitko Veta (CoRR, 2025)

Pathology Report Generation and Multimodal Representation Learning for Cutaneous Melanocytic Lesions. - Ruben T. Lucassen; Sander P. J. Moonemans; Tijn van de Luijtgaarden; Gerben E. Breimer; Willeke A. M. Blokx; Mitko Veta (CoRR, 2025)

PathoPainter: Augmenting Histopathology Segmentation via Tumor-aware Inpainting. - Hong Liu; Haosen Yang 003; Evi M. C. Huijben; Mark Schuiveling; Ruisheng Su; Josien P. W. Pluim; Mitko Veta (CoRR, 2025)

Adaptive Prototype Learning for Multimodal Cancer Survival Analysis. - Hong Liu; Haosen Yang 003; Federica Eduati; Josien P. W. Pluim; Mitko Veta (CoRR, 2025)

A Spatially-Aware Multiple Instance Learning Framework for Digital Pathology. - Hassan Keshvarikhojasteh; Mihail Tifrea; Sibylle Hess; Josien P. W. Pluim; Mitko Veta (CoRR, 2025)