Diana M. Sima1,
2, Sofie Van Cauter3, Yuqian Li4, Anca R.
Croitor-Sava1, 2, Uwe Himmelreich5, Sabine
Van Huffel1, 2
1Electrical
Engineering / ESAT-SCD, KU Leuven, Heverlee, Leuven, Belgium; 2Future
Health Department, iMinds, Heverlee, Leuven, Belgium; 3Department
of Radiology, University Hospitals Leuven, Leuven, Belgium; 4School
of Electronic Engineering, University of Electronic Science and Technology of
China, Chengdu, China; 5Department of Imaging & Pathology,
Biomedical MRI Unit, KU Leuven, Leuven, Belgium
We propose and validate a new computational method for unsupervised tissue differentiation for brain tumor patients, based on short echo time 2D magnetic resonance spectroscopic imaging data, which takes into account possible spectral distortions due to significant Chemical Shift Displacement artifact.