Semiautomatic segmentation of brain exterior in magnetic resonance images driven by empirical procedures and anatomical knowledge
✍ Scribed by Andrew J. Worth; Nikos Makris; James W. Meyer; Verne S. Caviness Jr; David N. Kennedy
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 154 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1361-8415
No coin nor oath required. For personal study only.
✦ Synopsis
This work demonstrates encouraging results for increasing the automation of a practical and precise magnetic resonance brain image segmentation method. The intensity threshold for segmenting the brain exterior is determined automatically by locating the choroid plexus. This is done by finding peaks in a series of histograms taken over regions specified using anatomical knowledge. Intensity inhomogeneities are accounted for by adjusting the global intensity to match the white matter peak intensity in local regions. Automated results are incorporated into the established manually guided segmentation method by providing a trained expert with the automated threshold. The results from 20 different brain scans (over 1000 images) obtained under different conditions are presented to validate the method which was able to determine the appropriate threshold in ∼80% of the data.