Computer Aided Screening of Breast Cancer Based on the Processing of Mammograms

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Mammogram is considered to be the most reliable modality for the screening of breast cancer, and screening program using mammography has become popular for the detection of early breast cancer. Computer aided diagnosis (CAD) system for mammography has the possibility to be used as a second reader to increase reliability of mass screening. And development of CAD system for mammography has become one of the most important subjects of research in the area of medical image processing. CAD system for mammography consists of two subsystems in general.One of them is a tumor mass detection system and the other is a clustered microcalcification detection system. In this research, we have developed new methods to detect malignant tumors and clustered microcalcifications.In the tumor detection system, a nonlinear filter called Iris filter has been adopted to enhance rounded opacities on mammogram. A new boundary estimation method of tumor candidates and feature parameters to extract boundary characteristics of tumors have been adopted. In the clustered microcalcification detection system, morphological operation to detect microcalcifications has been developed. And adaptive processing is also adopted to keep the system optimum under various imaging conditions and patient variations.The system performance has been evaluated at National Cancer Center Hospital East.Mammograms taken from outpatients during the past one and a half years were used as unknown samples. The number of mammograms is 3812. The system performance was as follows.True positive detection rate and average number of false positives of the malignant tumor detection system were 88% and 1.34 per image, respectively. Those of the clustered microcalcification detection system were 94% and 0.39, respectively. These results show the effectiveness of proposed system..