Project 2.2 - Dynamic Deep Learning

We develop a framework for dynamic deep learning. This system can learn continuously from feedback from experts. It can learn easy concepts first and gradually learn complex tasks after having seen more data. The network will express its uncertainty and ask for feedback on cases it is uncertain about or has not seen before.

Project Leader

Radboud University Medical Center
Dr. Clarisa Sánchez Radboud University Medical Center clara.sanchezgutierrez@radboudumc.nl

Co-Applicants

Radboud University Medical Center
Prof.dr. Bram van Ginneken Radboud University Medical Center bram.vanginneken@radboudumc.nl
Amsterdam UMC
Dr. Ivana Išgum Amsterdam UMC i.isgum@amsterdamumc.nl

Researchers

Radboud University Medical Center
Cristina Gonzalez Gonzalo Radboud University Medical Center cristina.gonzalezgonzalo@radboudumc.nl
Radboud University Medical Center
Ecem Lago Radboud University Medical Center ecem.lago@radboudumc.nl
Amsterdam UMC
Jörg Sander Amsterdam UMC j.sander1@amsterdamumc.nl

Publications

2020

Ecem Sogancioglu,Keelin Murphy,Erdi Calli, Ernst Scholten, Steven Schalekamp, Bram van Ginneken

Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification Journal Article

IEEE Access, 8 , pp. 94631 - 94642, 2020, ISSN: 2169-3536.

Links | BibTeX

C. González-Gonzalo, B. Liefers, B. van Ginneken, C. I. Sánchez

Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks: application to color fundus images Journal Article Forthcoming

IEEE Transactions on Medical Imaging, Forthcoming.

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

2019

C. González-Gonzalo, V. Sánchez-Gutiérrez, P. Hernández-Martínez, I. Contreras, Y. T. Lechanteur, A. Domanian, B. van Ginneken, C. I. Sánchez

Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration Journal Article

Acta Ophthalmologica, 2019.

Abstract | Links | BibTeX

C. González-Gonzalo, B. Liefers, A. Vaidyanathan, H. J. van Zeeland, C. C. W. Klaver, C. I. Sánchez

Opening the “black box” of deep learning in automated screening of eye diseases Conference

Association for Research in Vision and Ophthalmology Annual Meeting. ARVO Vancouver, 2019.

Abstract | Links | BibTeX

J. Engelberts, C. González-Gonzalo, C. I. Sanchez, M. van Grinsven

Automatic Segmentation of Drusen and Exudates on Color Fundus Images using Generative Adversarial Networks Conference

Association for Research in Vision and Ophthalmology Annual Meeting. ARVO Vancouver, 2019.

Abstract | Links | BibTeX

J. Sander, B.D. de Vos, J.M. Wolterink, I. Išgum

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI Inproceedings

SPIE Medical Imaging, 2019.

Abstract | Links | BibTeX

2018

C. González-Gonzalo, B. Liefers, B. van Ginneken, C. I. Sánchez

Improving weakly-supervised lesion localization with iterative saliency map refinement Conference

Medical Imaging with Deep Learning. MIDL Amsterdam, 2018.

Abstract | Links | BibTeX