DSP in mammography

Breast cancer is the most frequently occurring cancer in females with no cure at present. Early detection offers the best chance of survival and mammography is used to screen the asymptomatic female population above fifty years of age. Computerized analysis of mammograms can assist radiologists to detect lesions or abnormalities. However, the entire digitized mammogram must first be segmented and analyzed prior to lesion detection. This paper summarizes work done at the Australian Research Centre for Medical Engineering (ARCME) to systematically and hierarchically segment mammograms as a precursor to lesion detection. The breast is first segmented from the non-breast background by polynomial modelling and subtraction of the latter region. The nipple, which is the only anatomical landmark, is then located using a sensitive feature set to search the breast border. The pectoral muscle is then identified by an adaptive edge detection/surface fitting algorithm. Finally, a systematic methodology is proposed for lesion search.