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Knowledge-Guided Deformable Registration
This project is no longer active.
Head: Takeo Kanade
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated center(s) / consortia:
 Medical Robotics Technology Center (MRTC)
 Vision and Autonomous Systems Center (VASC)
Project Homepage
The goal of this research is to match corresponding anatomical structures across individuals, and to detect possible pathologies. The current image data is Magnetic Resonance Imaging (MRI) of human brains. MRI datasets are volumetric images which provide 3-D anatomical information. They consist of 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.