Improving Clinical Diagnosis Through Change Detection in Mammography
Annual rept. 1 Sep 1999-31 Aug 2000
CATHOLIC UNIV OF AMERICA WASHINGTON DC
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Temporal change of mass lesions overtime is a key piece of information in computer-aided diagnosis of breast cancer and treatment monitoring. For a specific patient, change detection depends on the ability to align the images of the mammogram sequence to a common axis, and the ability to build up memory about the image scene overtime. The process of aligning images to a common axis is termed image registration. The image scene representation is called site model. In the second year of this project, we developed a novel registration technique to align temporal sequences of the same patient, to construct a scene memory or site model, with the ultimate goal of performing change detection. We developed 1 a new hybrid registration algorithm aimed at the registration of non-rigid objects with minimal a prior knowledge 2 a new change quantification metric based on the joint relative entropy between two images 3 a patient specific site model concept to image-guided lesion monitoring 4 a methodology to combine multiple transforms together to determine a composite image transform and 5 an improved statistical segmentation algorithm for sequences of images.
- Anatomy and Physiology
- Medicine and Medical Research
- Computer Programming and Software