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
University Medical Center Utrecht
Dr. Ivana Išgum University Medical Center Utrecht i.isgum@umcutrecht.nl

Researchers

University Medical Center Utrecht
Jörg Sander University Medical Center Utrecht j.sander@umcutrecht.nl

Publications

2019

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