Project 2.1 - Weakly Labeled Learning

We focus on deep learning with large amounts of images that are only weakly labeled (e.g. only overall diagnosis or treatment outcome is available). We develop techniques that exploit a small set of images with detailed annotations and a large pool of weakly or completely unlabeled data. We exploit shared representations between learning tasks with different localization levels and use active learning where medical experts are asked for feedback on automatically selected cases.

Project Leader

Eindhoven University of Technology
Prof.dr. Josien Pluim Eindhoven University of Technology j.pluim@tue.nl

Co-Applicants

Erasmus Medical Center
Dr. Marleen de Bruijne Erasmus Medical Center marleen.debruijne@erasmusmc.nl
Eindhoven University of Technology
Dr. Mitko Veta Eindhoven University of Technology M.Veta@tue.nl

Researchers

Eindhoven University of Technology
Suzanne Wetstein Eindhoven University of Technology s.c.wetstein@tue.nl
Eindhoven University of Technology
Friso Heslinga Eindhoven University of Technology f.g.heslinga@tue.nl
Erasmus Medical Center
Gerda Bortsova Erasmus Medical Center g.bortsova@erasmusmc.nl

Publications

2020

Gerda Bortsova, Daniel Bos, Florian Dubost, Meike W. Vernooij, M. Kamran Ikram, Gijs van Tulder, Marleen de Bruijne

Automated Assessment of Intracranial Carotid Artery Calcification in Non-Contrast CT Using Deep Learning Journal Article Forthcoming

Forthcoming.

BibTeX

Coen de Vente, Pieter Vos, Matin Hosseinzadeh, Josien Pluim, Mitko Veta

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-parametric MRI Journal Article Forthcoming

IEEE Transactions on Biomedical Engineering, Forthcoming.

Abstract | Links | BibTeX

Suzanne C Wetstein, Nikolas Stathonikos, Josien PW Pluim, Yujing J Heng, Natalie D ter Hoeve, Celien PH Vreuls, Paul J van Diest, Mitko Veta

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images Journal Article Forthcoming

arXiv, Forthcoming.

Abstract | Links | BibTeX

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 Journal Article

Translational Vision Science & Technology, 9 (48), 2020.

Abstract | Links | BibTeX

Kevin H. Kensler; Emily Z.F. Liu; Suzanne C. Wetstein; Allison M. Onken; Christina I. Luffman; Gabrielle M. Baker; Laura C. Collins; Stuart J. Schnitt; Vanessa C. Bret-Mounet; Mitko Veta; Josien P.W. Pluim; Ying Liu; Graham A. Colditz; A. Heather Eliassen; Susan E. Hankinson; Rulla M. Tamimi; Yujing J. Heng

Automated quantitative measures of terminal duct lobular unit involution and breast cancer risk Journal Article

Cancer epidemiology, biomarkers & prevention, 29 (11), 2020.

Abstract | Links | BibTeX

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 Journal Article

PLoS ONE, 15 (4), pp. e0231653, 2020.

Abstract | Links | BibTeX

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 Conference

2020.

Abstract | Links | BibTeX

C. González-Gonzalo, S. C. Wetstein, G. Bortsova, B. Liefers, B. van Ginneken, C. I. Sánchez

Are adversarial attacks an actual threat for deep learning systems in real-world eye disease screening settings? Conference

European Society of Retina Specialists, 2020.

Abstract | Links | BibTeX

F.G. Heslinga, J.P.W. Pluim, A.J. Houben, M.T. Schram, R.M. Henry, C.D. Stehouwer, M.J. Van Greevenbroek, T.T. Berendschot, M. Veta

Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study Inproceedings

Medical Imaging 2020: Computer-Aided Diagnosis, pp. 113141N, International Society for Optics and Photonics, 2020.

Abstract | Links | BibTeX

2019

Ruwan Tennakoon, Gerda Bortsova, Silas Ørting, Amirali K Gostar, Mathilde MW Wille, Zaigham Saghir, Reza Hoseinnezhad, Marleen de Bruijne, Alireza Bab-Hadiashar

Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem Journal Article

IEEE Transactions on Medical Imaging, 39 (4), pp. 854-865, 2019.

Abstract | Links | BibTeX

Christina I. Luffman, Suzanne C. Wetstein, Allison M. Onken, Michael E. Pyle, Kevin H. Kensler, Ying Liu, Josien P. Pluim, Mitko Veta, Stuart J. Schnitt, Rulla M. Tamimi, Gabrielle M. Baker, Laura C. Collins, Yu Jing Heng

Assessing Breast Terminal Duct Lobular Unit Involution: A Computational Pathology Approach Conference

Abstracts and Case Studies From the College of American Pathologists 2019 Annual Meeting (CAP19), 143 (9), Archives of Pathology & Laboratory Medicine, 2019.

Links | BibTeX

Allison M. Onken, Suzanne Wetstein, Michael Pyle, Josien Pluim, Stuart J. Schnitt, Gabrielle M Baker, Laura C. Collins, Rulla Tamimi, Mitko Veta, Yujing Jan Heng

Deep Learning Networks to Segment and Detect Breast Terminal Duct Lobular Units, Acini, and Adipose Tissue: A Step Toward the Automated Analysis of Lobular Involution as a Marker for Breast Cancer Risk Conference

United States and Canadian Academy of Pathology (USCAP), 2019.

Abstract | BibTeX

Gerda Bortsova, Florian Dubost, Laurens Hogeweg, Ioannis Katramados, Marleen de Bruijne

Semi-supervised medical image segmentation via learning consistency under transformations Inproceedings

International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 810-818, Springer, Cham, 2019.

Abstract | Links | BibTeX

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 Inproceedings

SPIE Medical Imaging, 2019.

Abstract | Links | BibTeX

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 Inproceedings

SPIE Medical Imaging, 2019.

Abstract | Links | BibTeX

2018

G. Bortsova, F. Dubost, S. Ørting, I. Katramados, L. Hogeweg, L. Thomsen, M. Wille, M. de Bruijne

Deep learning from label proportions for emphysema quantification Inproceedings

International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 768–776, Springer, Cham, 2018.

Abstract | Links | BibTeX