CAD system for full-digital mammography and its evaluation

The purpose of this study is to develop a clinical intelligent workstation for computer-aided diagnosis (CAD) of breast cancer using fall digital mammography. It consists of a clinical workstation and Fuji Computed Radiography 9000 System. New image processing methods to extract tumor masses and clustered microcalcifications have been developed and implemented in the CAD system. A new filter called Iris Filter has been developed to detect tumor candidates. It realizes reliable detection of tumor candidates regardless of their sizes and their contrast against their background on mammograms. And a new method based on mathematical morphology has been developed to detect microcalcifications. It is adaptive to the imaging conditions of mammograms. One thousand, two hundred and twelve CR images, which include 240 malignant tumors, were used to test the performance of the system. The sensitivity for malignant tumors was 90.5% and the average number of false positives per image were only 1.3. The true positive detection rate for clustered microcalcifications was 89.2% and the average number of false positives per image were 0.36. The high true positive rates and the low false positive detection characterize the proposed full-digital CAD system, which shows the possibility of practical application of computer aided diagnosis of breast cancer.