Project 1.3 - Deep Transfer Learning

For real world systems training data has been acquired with slightly different acquisition protocols, different scanners, or from a different patient population. To still learn robustly, we will develop deep transfer learning technology where the domain transfer is addressed in the representation learning step for which we use different coupled network architectures.

Project Leader

Erasmus Medical Center
Dr. Marleen de Bruijne Erasmus Medical Center marleen.debruijne@erasmusmc.nl

Co-Applicants

Amsterdam UMC
Dr. Ivana Išgum Amsterdam UMC i.isgum@amsterdamumc.nl
University of Amsterdam
Prof.dr. Max Welling University of Amsterdam m.welling@uva.nl

Researchers

University of Amsterdam
Maximilian Ilse University of Amsterdam m.ilse@uva.nl
Erasmus Medical Center
Kimberlin van Wijnen Erasmus Medical Center k.vanwijnen@erasmusmc.nl
Amsterdam UMC
Julia Noothout Amsterdam UMC j.m.h.noothout@amsterdamumc.nl

Publications

2019

Julia M.H. Noothout, Bob D. de Vos, Jelmer M. Wolterink, Richard A.P. Takx, Tim Leiner, Ivana Išgum

Deep Learning for Automatic Landmark Localization in CTA for Transcatheter Aortic Valve Implantation Conference

Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX

2018

J.M.H. Noothout, B.D de Vos, J.M. Wolterink, T. Leiner, I. Isgum

CNN-based Landmark Detection in Cardiac CTA Scans Inproceedings

Medical Imaging with Deep Learning. MIDL Amsterdam, 2018.

Abstract | Links | BibTeX