Automated brain segmentation from single slice, multislice, or whole-volume MR scans using prior knowledge.
OBJECTIVE
An automated procedure has been developed to isolate the brain in single/multislice or whole-volume MR images obtained from various sequences.


METHODS
T1-weighted, T2-weighted, and inversion recovery images were acquired. The brain segmentation procedure employed (A) a knowledge base that held generic information about the brain in the three orthogonal views and (B) a texture definition and intensity characteristics of features within the head. The brain was segmented by selectively blurring scans using components of B; contour following with region growing was initiated until the isolated feature satisfied the measurements in A.


RESULTS
The brain was segmented automatically from 210 subjects (whole volume) and 52 subjects (multi/single slice). Detailed analysis of seven segmented brains showed that < 0.8% of the contour pixels were erroneously identified. Whole-volume head scans consisting of 140 x 256 x 256 pixels were segmented in < 30 min.


CONCLUSIONS
A robust, fast, and efficient procedure has been developed to segment the brain from MR images.
Saeed
N
N
Picker Research Laboratory, GEC Hirst Research Centre, Borehamwood, England.
Hajnal
J V
JV
Oatridge
A
A
D000328:Adult; D000368:Aged; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged