Segmentation of MRI brain scans into gray matter white matter and CSF

摘要

An algorithm is described that can separate gray matter, white matter and CSF in brain scans taken with 3DFFT T$-1$/- weighted gradient echo magnetic resonance imaging. Although the algorithm is fully automated, it requires brain contours as input that utilize user-defined features. The inter- and intra-operator errors stemming from the variability of the contour definition and affecting the segmentation were assessed by using coronal brain scans of 19 subjects. The inter-operator errors were (1.61 plus or minus 2.38)% (P equals 0.01) for gray matter, (0.31 plus or minus 2.06)% (P equals 0.53) for white matter and (0.28 plus or minus 3.84)% (P equals 0.76) for cerebrospinal fluid (CSF). the intra- operator error was (0.28 plus or minus 0.55)% (P greater than 0.04) for gray matter, (0.40 plus or minus 0.37)% (P equals 0.0002) for white matter and (0.26 plus or minus 1.31)% (P equals 0.39) for CSF.