AUTHOR=Scully Mark , Anderson Blake , Lane Terran , Gasparovic Charles , Magnotta Vince , Sibbitt Wilmer , Roldan Carlos , Kikinis Ron , Bockholt Henry J. TITLE=An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus JOURNAL=Frontiers in Human Neuroscience VOLUME=Volume 4 - 2010 YEAR=2010 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2010.00027 DOI=10.3389/fnhum.2010.00027 ISSN=1662-5161 ABSTRACT=

We demonstrate an automated, multi-level method to segment white matter brain lesions and apply it to lupus. The method makes use of local morphometric features based on multiple MR sequences, including T1-weighted, T2-weighted, and fluid attenuated inversion recovery. After preprocessing, including co-registration, brain extraction, bias correction, and intensity standardization, 49 features are calculated for each brain voxel based on local morphometry. At each level of segmentation a supervised classifier takes advantage of a different subset of the features to conservatively segment lesion voxels, passing on more difficult voxels to the next classifier. This multi-level approach allows for a fast lesion classification method with tunable trade-offs between sensitivity and specificity producing accuracy comparable to a human rater.