Detection of Mass on Dense Mammogram
Seung-Hwa Yu, Seung-Mu No, Jongwon Park · Journal of the Institute of Electronics Engineers of Korea · 2001
This paper proposed automated methods for the detection of breast mass. We analysed characteristic of the mass by using the features on mammograms. The homogeneity was used to distinguish mass and abnormal homogeneous tissue from the Cooper's ligament and multiple threshold method was used to deal with the high density candidates. By using the 8-connectivity, the first step candidates were selected. We generated the dualistic images of each candidate in which we regard the gray value as topographic height information. From these candidates, the second candidates were selected by comparing the circularity and the distribution rates. The final detection was done with the method in which we generated the template of each candidate and compared each other. From these methods, we grade the order from the candidate. We applied the algorithm to the 136 mammograms and compared to the radiologist's outlines of the leisions. The detection resulted that the sensitivity of the proposed methods was 93.38% and 97.63% FP(False positive) which we can segmented mass in the first grade in the 124 cases.