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In this study, we developed an automatic extraction scheme for the precise recognition of the contours of masses on digital mammograms in order to improve a computer-aided diagnosis (CAD) system. We propose a radial-searching contour extraction method based on a modified active contour model (ACM). In this technique, after determining the central point of a mass by searching for the direction of the density gradient, we arranged an initial contour at the central point, and the movement of a control point was limited to directions radiating from the central point. Moreover, it became possible to increase the extraction accuracy by sorting out the pixel used for processing and using two images-an edge-intensity image and a degree-of-separation image defined based on the pixel-value histogram-for calculation of the image forces used for constraints on deformation of the ACM. We investigated the accuracy of the automated extraction method by using 53 masses with several "difficult contours" on 53 digitized mammograms. The extraction results were compared quantitatively with the "correct segmentation" represented by an experienced physician's sketches. The numbers of cases in which the extracted region corresponded to the correct region with overlap ratios of more than 81 and 61% were 30 and 45, respectively. The initial results obtained with this technique show that it will be useful for the segmentation of masses in CAD schemes.

The Japanese NPO Central Committee on Quality Control of Mammographic Screening has initiated international exchange activities regarding quality control of mammographic screening with the concerned organizations in East Asian countries with the objective of contributing to reducing breast cancer mortality in the region. This paper describes the status of the international exchanges that are being carried out in various East Asian countries in relation to mammography and also discusses future aspects.