Detecting breast cancer from infrared images by asymmetry analysis

Infrared imaging of the breast (also called thermography) has shown effective results in both risk assessment and prognostic determination of breast cancer. This paper proposes an automated approach to detect asymmetric abnormalities in thermograms. Canny edge detector is first used to derive the edges from the original image. Hough transform is then applied to the edge image to recognize the four feature curves, which include the left and the right body boundary curves, and the two parabolic curves indicating the lower boundaries of the breasts. Segmentation is conducted based on the intersection of the two parabolic curves and the body boundaries. Bezier histogram is then derived from each segment. Curvature information is finally computed from the histogram to be used to easily indicate the asymmetry.