In this study, an automatic 3-D region-based CADe system for ABUS images was proposed. At first, the fast 3-D mean shift method was adopted to segment 3-D image into several regions. Subsequently, the FCM method was applied to classify these regions into different classes according to their intensities. Because the intensities of the tumor regions were usually darker than that of the other tissue regions, the dark regions were regarded as the suspicious tumor regions in our study.
Due to many FPs in the suspicious tumor regions, seven features were used to reduce these FPs. In the experiments, the sensitivity of the CADe system was 89.04%
(130/146 lesions) with 4.92 FPs. The results show that the 3-D region-based CADe system could perform well and provide the reliable diagnosis.
Although the final results of tumor detection are acceptable, the proposed method could be further improved. After the FP reduction, some ribs are still miss-classified to be the tumors since the segmented regions of these ribs are tumor-alike. Further features should be used to discriminate these ribs from tumors.
Because the ribs usually locates below the central horizontal of the A-view slice image, the features that concern with the position of the segmented region may be useful to further reduce the FP rate of the detection system.
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