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Medical Image Analysis
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June 7, 2019
Corrigendum to "Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge" [Medical Image Analysis, 54 (2019) 111--121]
Mitko Veta
European Heart Journal
|
May 17, 2021
Can automatic image analysis replace the pathologist in cardiac allograft rejection diagnosis?
Mitko Veta, Paul J van Diest, Aryan Vink
IEEE Transactions on Bio-Medical Engineering
|
August 14, 2020
Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols
Linde S Hesse, Grey Kuling, Mitko Veta, et al.
Journal of Pathology Informatics
|
July 17, 2013
Going fully digital: Perspective of a Dutch academic pathology lab
Nikolas Stathonikos, Mitko Veta, André Huisman, et al.
IEEE Transactions on Bio-Medical Engineering
|
May 13, 2020
Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI
Coen de Vente, Pieter Vos, Matin Hosseinzadeh, et al.
Frontiers in Medicine
|
August 6, 2019
Learning Domain-Invariant Representations of Histological Images
Maxime W Lafarge, Josien P W Pluim, Koen A J Eppenhof, et al.
IEEE Transactions on Bio-Medical Engineering
|
April 25, 2014
Breast cancer histopathology image analysis: a review
Mitko Veta, Josien P W Pluim, Paul J van Diest, et al.
Plos One
|
December 5, 2025
Beyond accuracy: Quantifying the reliability of multiple instance learning for whole slide image classification
Hassan Keshvarikhojasteh, Marc Aubreville, Christof A Bertram, et al.
IEEE Transactions on Medical Imaging
|
November 22, 2019
Progressively Trained Convolutional Neural Networks for Deformable Image Registration
Koen A J Eppenhof, Maxime W Lafarge, Mitko Veta, et al.
Translational Vision Science & Technology
|
September 5, 2020
Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks
Friso G Heslinga, Mark Alberti, Josien P W Pluim, et al.
Page
of 7
Search research articles
Search
Showing results (1-10 of 67) with videos related to
Sort By:
Page
of 7
Medical Image Analysis
|
June 7, 2019
Corrigendum to "Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge" [Medical Image Analysis, 54 (2019) 111--121]
Mitko Veta
European Heart Journal
|
May 17, 2021
Can automatic image analysis replace the pathologist in cardiac allograft rejection diagnosis?
Mitko Veta, Paul J van Diest, Aryan Vink
IEEE Transactions on Bio-Medical Engineering
|
August 14, 2020
Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols
Linde S Hesse, Grey Kuling, Mitko Veta, et al.
Journal of Pathology Informatics
|
July 17, 2013
Going fully digital: Perspective of a Dutch academic pathology lab
Nikolas Stathonikos, Mitko Veta, André Huisman, et al.
IEEE Transactions on Bio-Medical Engineering
|
May 13, 2020
Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI
Coen de Vente, Pieter Vos, Matin Hosseinzadeh, et al.
Frontiers in Medicine
|
August 6, 2019
Learning Domain-Invariant Representations of Histological Images
Maxime W Lafarge, Josien P W Pluim, Koen A J Eppenhof, et al.
IEEE Transactions on Bio-Medical Engineering
|
April 25, 2014
Breast cancer histopathology image analysis: a review
Mitko Veta, Josien P W Pluim, Paul J van Diest, et al.
Plos One
|
December 5, 2025
Beyond accuracy: Quantifying the reliability of multiple instance learning for whole slide image classification
Hassan Keshvarikhojasteh, Marc Aubreville, Christof A Bertram, et al.
IEEE Transactions on Medical Imaging
|
November 22, 2019
Progressively Trained Convolutional Neural Networks for Deformable Image Registration
Koen A J Eppenhof, Maxime W Lafarge, Mitko Veta, et al.
Translational Vision Science & Technology
|
September 5, 2020
Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks
Friso G Heslinga, Mark Alberti, Josien P W Pluim, et al.
Page
of 7