25 April 1997 Segmentation of MRI brain scans into gray matter, white matter, and CSF
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Abstract
An algorithm is described that can separate gray matter, white matter and CSF in brain scans taken with 3DFFT T1- 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.
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Tamas Sandor, Tamas Sandor, Hoo-Tee Ong, Hoo-Tee Ong, Vladimir I. Valtchinov, Vladimir I. Valtchinov, Marilyn Albert, Marilyn Albert, Ferenc A. Jolesz, Ferenc A. Jolesz, } "Segmentation of MRI brain scans into gray matter, white matter, and CSF", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274106; https://doi.org/10.1117/12.274106
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