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Mitko Veta
Tytuł
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Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ...
Jama 318 (22), 2199-2210, 2017
28382017
Breast cancer histopathology image analysis: A review
M Veta, JPW Pluim, PJ Van Diest, MA Viergever
IEEE transactions on biomedical engineering 61 (5), 1400-1411, 2014
7292014
Assessment of algorithms for mitosis detection in breast cancer histopathology images
M Veta, PJ Van Diest, SM Willems, H Wang, A Madabhushi, A Cruz-Roa, ...
Medical image analysis 20 (1), 237-248, 2015
4972015
Automatic nuclei segmentation in H&E stained breast cancer histopathology images
M Veta, PJ Van Diest, R Kornegoor, A Huisman, MA Viergever, ...
PloS one 8 (7), e70221, 2013
4432013
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ...
Medical image analysis 54, 111-121, 2019
2752019
Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ...
IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021
2652021
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging
Z Xiong, Q Xia, Z Hu, N Huang, C Bian, Y Zheng, S Vesal, N Ravikumar, ...
Medical image analysis 67, 101832, 2021
2072021
Going fully digital: Perspective of a Dutch academic pathology lab
N Stathonikos, M Veta, A Huisman, PJ van Diest
Journal of Pathology Informatics, 2013
1952013
Roto-translation covariant convolutional networks for medical image analysis
EJ Bekkers, MW Lafarge, M Veta, KAJ Eppenhof, JPW Pluim, R Duits
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
1752018
Adversarial training and dilated convolutions for brain MRI segmentation
P Moeskops, M Veta, MW Lafarge, KAJ Eppenhof, JPW Pluim
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
1672017
Domain-adversarial neural networks to address the appearance variability of histopathology images
MW Lafarge, JPW Pluim, KAJ Eppenhof, P Moeskops, M Veta
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
1342017
Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images
M Veta, A Huisman, MA Viergever, PJ van Diest, JPW Pluim
2011 IEEE international symposium on biomedical imaging: from nano to macro …, 2011
1292011
Deep learning regression for prostate cancer detection and grading in bi-parametric MRI
C De Vente, P Vos, M Hosseinzadeh, J Pluim, M Veta
IEEE Transactions on Biomedical Engineering 68 (2), 374-383, 2020
1182020
Deformable image registration using convolutional neural networks
KAJ Eppenhof, MW Lafarge, P Moeskops, M Veta, JPW Pluim
Medical Imaging 2018: Image Processing 10574, 192-197, 2018
1162018
Mitosis counting in breast cancer: Object-level interobserver agreement and comparison to an automatic method
M Veta, PJ Van Diest, M Jiwa, S Al-Janabi, JPW Pluim
PloS one 11 (8), e0161286, 2016
1122016
Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer
M Veta, R Kornegoor, A Huisman, AHJ Verschuur-Maes, MA Viergever, ...
Modern pathology 25 (12), 1559-1565, 2012
882012
Mitosis domain generalization in histopathology images—the MIDOG challenge
M Aubreville, N Stathonikos, CA Bertram, R Klopfleisch, N Ter Hoeve, ...
Medical Image Analysis 84, 102699, 2023
802023
Adversarial attack vulnerability of medical image analysis systems: Unexplored factors
G Bortsova, C González-Gonzalo, SC Wetstein, F Dubost, I Katramados, ...
Medical Image Analysis 73, 102141, 2021
732021
Roto-translation equivariant convolutional networks: Application to histopathology image analysis
MW Lafarge, EJ Bekkers, JPW Pluim, R Duits, M Veta
Medical Image Analysis 68, 101849, 2021
732021
Deep‐learning‐based preprocessing for quantitative myocardial perfusion MRI
CM Scannell, M Veta, ADM Villa, EC Sammut, J Lee, M Breeuwer, ...
Journal of Magnetic Resonance Imaging 51 (6), 1689-1696, 2020
692020
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