Automated brain segmentation from single slice, multislice, or whole-volume MR scans using prior knowledge
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Published on: July 19, 2019
N Saeed1, J V Hajnal, A Oatridge
1Picker Research Laboratory, GEC Hirst Research Centre, Borehamwood, England.
Purpose:
An automated procedure has been developed to isolate the brain in single/multislice or whole-volume MR images obtained from various sequences.
Method:
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.
Conclusion:
A robust, fast, and efficient procedure has been developed to segment the brain from MR images.
