<title>Automated detection of masses and clustered microcalcifications on mammograms</title>

We are developing automated-detection schemes for the masses and clustered microcalcifications on laser-digitized mammograms (0.1 mm, 10-bit resolution, 2000 X 2510) by using a conventional workstation. The purpose of this paper is to provide an overview of our recent schemes and to evaluate the current performance of the schemes. The fully automated computer system consists of several parts such as the extraction of breast region, detection of masses, detection of clustered microcalcifications, classification of the candidates, and the display of the detected results. Our schemes tested with more than 200 cases of Japanese women achieved an about 95% (86%) true-positive rate with 0.61 (0.55) false-positive masses (clusters) per image. It was found that the automated method has the potential to aid physicians in screening mammograms for breast tumors. Initial results for the mammograms digitized with the pixel sizes of 25, 50, and 100 micrometers are also discussed, in which a genetic algorithm (GA) technique was applied to the detection filter for the microcalcifications. It was indicated from the experiment with a breast phantom that 100- micrometers pixel size is not enough for the computer detection of microcalcifications, and it seems that at least 50-micrometers pixel size is required.