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Open Ground Truth Training Network : Magnetic resonance image simulation for training and validation of image analysis algorithms

Objective

This action aims to optimally prepare three young researchers for the evolving medical imaging world by offering a unique set of targeted interdisciplinary training and research assignments in the areas of anatomy, pathology, imaging techniques, quantitative image analysis and segmentation, Magnetic Resonance (MR) physics and MR image simulation.
MR imaging is the major imaging modality for brain and spine anatomy and pathology. A clear trend can be observed from visual to computer-assisted diagnosis by quantification of disease-specific biomarkers, derived from the MR images. The major components in image quantification applications are tissue and organ segmentation and classification. Manual segmentation is too tedious and cumbersome for daily clinical practice and would lead to large inter-user variability. Much research is therefore performed on automatic segmentation techniques. Training, validation and benchmarking of these techniques is currently impeded by the lack of MR image databases with exact reference segmentations.
The research will follow an innovative approach to overcome the current barriers for wide uptake of automatic segmentation. By combining mathematical organ models with physical and biological tissue properties and image simulation methods, substantial public image databases will be established providing ample MR images with ground truth (exact) segmentations, by which fast and accurate optimization and validation of image segmentation algorithms will be enabled.
Based on sound career development plans, and coached by experienced supervisors a training is offered by leading image analysis research groups from Philips (global leader in medical imaging) and the Eindhoven University of Technology (world-wide recognized authority in education and research on image analysis, esp. on MRI) and supported by researchers from leading clinical centers as UMC Utrecht, TU Munich, Kings College London and the German Center for Neurodegenerative Diseases.

Field of science

  • /natural sciences/computer and information sciences/databases
  • /medical and health sciences/basic medicine/pathology
  • /medical and health sciences/clinical medicine/radiology/medical imaging

Call for proposal

H2020-MSCA-ITN-2017
See other projects for this call

Funding Scheme

MSCA-ITN-EID - European Industrial Doctorates

Coordinator

TECHNISCHE UNIVERSITEIT EINDHOVEN
Address
Groene Loper 3
5612 AE Eindhoven
Netherlands
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 766 122,84

Participants (1)

PHILIPS GMBH
Germany
EU contribution
€ 0
Address
Rontgenstrasse 22
22335 Hamburg
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)