Project 1.1 - High Dimensional Data

We develop deep learning techniques and efficient architectures for quantitative analysis of 4- and 5-D medical images that make optimal use of additional dimensions and apply them to cardiac spectral CT and MRI and sequential 4D chest CT.

Project Leader

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

Co-Applicants

Radboud University Medical Center
Prof.dr. Bram van Ginneken Radboud University Medical Center bram.vanginneken@radboudumc.nl
University of Amsterdam
Prof.dr. Max Welling University of Amsterdam m.welling@uva.nl
University Medical Center Utrecht
Prof.dr.ir. Max Viergever University Medical Center Utrecht M.Viergever@umcutrecht.nl
University Medical Center Utrecht
Prof.dr. Tim Leiner University Medical Center Utrecht T.Leiner@umcutrecht.nl

Researchers

Radboud University Medical Center
Nikolas Lessmann Radboud University Medical Center nikolas.lessmann@radboudumc.nl
University Medical Center Utrecht
Dr. Bob de Vos University Medical Center Utrecht B.D.deVos-2@umcutrecht.nl
University Medical Center Utrecht
Steffen Bruns University Medical Center Utrecht s.bruns@umcutrecht.nl
University Medical Center Utrecht
Robbert van Hamersvelt University Medical Center Utrecht R.W.vanHamersvelt-3@umcutrecht.nl

Publications

2019

R.W. van Hamersvelt, I. Išgum, P.A. de Jong, M.J. Cramer, G.E. Leenders, M.J. Willemink, M. Voskuil, T. Leiner

Application of speCtraL computed tomogrAphy to impRove specIficity of cardiac compuTed tomographY (CLARITY study): Rationale and Design Journal Article

BMJ Open, 9 (3), pp. e025793, 2019.

Abstract | Links | BibTeX

S. Bruns, J.M. Wolterink, R.W. van Hamersvelt, M. Zreik, T. Leiner, I. Išgum

Improving myocardium segmentation in cardiac CT angiography using spectral information Inproceedings

SPIE Medical Imaging, 2019.

Abstract | Links | BibTeX