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Master theses

Current and past ideas and concepts for Master Theses.

Big data and deep learning to improve automated MR image quantification

Subject

Automated quantification of MR images

Kind of work

- Development of a Python pipeline to apply deep learning on a large database of MR images (manually checked) to quantify brain volumes (Grey matter, white matter, ...)
- Development of a Python pipeline to apply deep learning on a large database of MR images (manually checked) to quantify lesions caused by Multiple Sclerosis
- Validation on data from different scanners

Framework of the Thesis

This project will be executed in collaboration with IcoMetrix N.V. (www.icometrix.com). IcoMetrix is a spin-off company from KULeuven and UAntwerpen and focusses on the development of automated image processing. The automated quantification of MR images provides the radiologist with unique information that would not be used on visual inspection. Since its incorporation, IcoMetrix has analysed thousands of MR images, comprising a unique database that allows to develop novel image processing through the application of deep learning.

Number of Students

1

Expected Student Profile

- Experience in Python (or Matlab)
- The student should be willing to work (from time to time) from Leuven

Promotor

Dr. Ir. Jef Vandemeulebroucke

+32 (0)2 629 1033

jefvdmb@etrovub.be

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