Brain tissue segmentation algorithms applied on magnetic resonance imaging (MRI) data lack a ground truth for evaluating their performance. For this purpose, an anatomical brain phantom prototype mimicking T1 relaxation times and the complex 3D geometry of the human brain was created for use with MRI and computed tomography (CT). A scan-rescan experiment showed a low within-session variability of white matter (WM) and grey matter (GM) volumes when MRI images of the phantom were segmented with a commonly used software. Compared to the ground truth volumes derived from CT, the software overestimated the WM, while the GM was slightly underestimated.
This abstract and the presentation materials are available to members only; a login is required.