Abstract
Breast cancer has become the third leading cause of death for women in Taiwan. For clinical pathologists, the grading criteria: Nottingham Modification of the Bloom-Richardson (NBR) System based on histological pathology is a gold standard to assess the lesion severity of the invasive ductal carcinoma. The grading indices for the disease based on NBR include tubular formation, pleomorphism, and mitotic count. Because the manual grading is measured depending on qualitative analysis, it usually causes a big workload due to its various variability. The major goal of this work is to extend our previous work and propose a computer-aided-diagnosis system to assess quantitatively the severity of the breast carcinoma. To this end, it first analyzes the H&E stained slide images of the breast specimen using a series of image processing operations to extract feature parameters related to morphometry of mammary tissue, and hyperplasia degrees of nucleus, and mitotic count of nuclei based on histology and cytology, and choosing important features with feature selection, and identify the scores using support vector machine finally. Experimental results reveal that the proposed system not only can obtain satisfactory performance, but also provide histological grade and prognosis information for clinical pathologists to improve the efficiency of diagnosis.
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Acknowledgment
This work was supported by a grant from Ministry of Science and Technology, R.O.C under a contract MOST 105-2221-E-415-020-MY2.
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Ko, CC., Chen, CY., Lin, JH. (2019). A Computer-Aided-Grading System of Breast Carcinoma: Pleomorphism, and Mitotic Count. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_81
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DOI: https://doi.org/10.1007/978-981-13-9190-3_81
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