Medical Image – Atlas Registration Using Deformable Models for Anomaly Detection

Abstract

We introduce a system that automatically segments and classifies structures in brain MRI volumes. It segments 144 structures of a 256x256x124 voxel image in 18 minutes on an SGI computer with four 194 MHz R10K processors. The algorithm uses an atlas, a hand segmented and classified MRI of a normal brain, which is warped in 3-D using a hierarchical deformable registration algorithm until it closely matches the subject. This customized atlas contains the segmentation and classification of the subject's anatomical structures. The system has processed 198 MRIs of normal brains, and 3 MRIs and 1 CT of brains with pathologies. Quantitative evaluations yield high segmentation accuracy. Combined with domain knowledge, the registration algorithm is able of detecting asymmetries and abnormal variations in the subject's data that indicate the existence and location of pathologies.