Mitko Veta

According to our database, Mitko Veta authored at least 58 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Shan-E-Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Xiuli Liu, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi

IEEE J. Biomed. Health Informatics, March, 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, 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

Medical Image Anal., 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

Multi-head Attention-based Deep Multiple Instance Learning.

Hassan Keshvarikhojasteh, Josien P. W. Pluim, Mitko Veta

CoRR, 2024

WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide images.

Hong Liu, Haosen Yang, Paul J. van Diest, Josien P. W. Pluim, 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

Tissue Cross-Section and Pen Marking Segmentation in Whole Slide Images.

Ruben T. Lucassen, Willeke A. M. Blokx, Mitko Veta

CoRR, 2024

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

Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound.

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

IEEE J. Biomed. Health Informatics, September, 2023

Mitosis domain generalization in histopathology images - The MIDOG challenge.

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

Medical Image Anal., 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

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, Shan E Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Thomas Watson, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi

CoRR, 2023

Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images.

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

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

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

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, 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

CoRR, 2022

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

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, 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

IEEE Trans. Medical Imaging, 2021

Editorial Computational Pathology.

Francesco Ciompi, Mitko Veta, Jeroen van der Laak, Nasir M. Rajpoot

IEEE J. Biomed. Health Informatics, 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

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

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

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

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

CoRR, 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

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

Proceedings of the Ophthalmic Medical Image Analysis - 8th International Workshop, 2021

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

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

Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology.

Maxime W. Lafarge, Josien P. W. Pluim, Mitko Veta

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

A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging.

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

CoRR, 2020

Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation.

Cian M. Scannell, Amedeo Chiribiri, Mitko Veta

Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 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

Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 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

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

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

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis.

Dragan Bosnacki, Natal A. W. van Riel, Mitko Veta

Proceedings of the Automated Reasoning for Systems Biology and Medicine, 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, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Josien P. W. Pluim

Medical Image Anal., 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

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, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, 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-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

Automatic cardiac landmark localization by a recurrent neural network.

Mike van Zon, Mitko Veta, Shuo Li

Proceedings of the Medical Imaging 2019: Image Processing, 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

Proceedings of the Medical Imaging 2019: Image Processing, 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

Proceedings of the Medical Imaging 2019: Digital Pathology, 2019

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

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

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, 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

CoRR, 2018

Deformable image registration using convolutional neural networks.

Koen A. J. Eppenhof, Maxime W. Lafarge, Pim Moeskops, Mitko Veta, Josien P. W. Pluim

Proceedings of the Medical Imaging 2018: Image Processing, 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

Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Inferring a third spatial dimension from 2D histological images.

Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

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

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 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

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Exploring the Similarity of Medical Imaging Classification Problems.

Veronika Cheplygina, Pim Moeskops, Mitko Veta, Behdad Dashtbozorg, Josien P. W. Pluim

Proceedings of the Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2017

2016

Cutting Out the Middleman: Measuring Nuclear Area in Histopathology Slides Without Segmentation.

Mitko Veta, Paul J. van Diest, Josien P. W. Pluim

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015

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, 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

Medical Image Anal., 2015

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

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

2013

Detecting mitotic figures in breast cancer histopathology images.

Mitko Veta, Paul J. van Diest, Josien P. W. Pluim

Proceedings of the Medical Imaging 2013: Digital Pathology, 2013

2011

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

Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011