The current image data is Magnetic Resonance Imaging (MRI) of human brains. MRI datasets are volumetric images which provide 3-D information of the anatomy. They are represented as parallel cross-sections scanned along one of three principal axes.
The current approach is to deform a hand-segmented and labelled atlas (Courtesy of Harvard Medical School/Brigham and Women's Hospital) to match a patient's brain, so as to segment and label the patient's anatomical structures using information derived from the atlas.
The algorithm applies a hierarchy of deformable models to the atlas to match with the patient at increasing accuracy.
A prototype, ADORE (Anomaly Detection thrOugh REgistration), is developed to employ the registration algorithm to detect pathologies that cause morphological changes in the brain.
For details, please refer to the paper: "Anomaly Detection through Registration" (1.8MB compressed), Mei Chen, Takeo Kanade, Henry A. Rowley, Dean Pomerleau, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June, 1998.
