Abstract.Mammographic risk assessment provides an indication of the likelihood of women developing breast cancer. A number of mammographic image based classification methods have been developed, such as Wolfe, Boyd, BI-RADS and Tabár based assessment. We provide a comparative study of these four approaches. Results on the full MIAS database are presented, which indicate strong correlation (Spearman's > 0.9) between Wolfe, Boyd and BI-RADS based classification, whilst the correlation with Tabár based classification is less straight forward (Spearman's < 0.5, but low correlations mainly caused by one of the classes).
Nuclei segmentation of the epithelial cells of a Pap smear image is an important step in order to have correct morphometric measures. This task is non trivial due to the complexities of the Pap smear images. Our paper presents a novel method on nuclei segmentation using morphological operation and watershed transformation. The proposed segmentation method was evaluated with respect to its nuclei area and its shape-similarity in comparison to the pathologist truth. It showed that the segmentation results are promising and it can be used for further analysis such as cell quantification or abnormality cell detection.
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