  Early detection and prognosis of breast cancer are feasible by utilizing
histopathological grading of biopsy specimens. This research is focused on
detection and grading of nuclear pleomorphism in histopathological images of
breast cancer. The proposed method consists of three internal steps. First,
unmixing colors of H&E is used in the preprocessing step. Second, nuclei
boundaries are extracted incorporating the center of cancerous nuclei which are
detected by applying morphological operations and Difference of Gaussian filter
on the preprocessed image. Finally, segmented nuclei are scored to accomplish
one parameter of the Nottingham grading system for breast cancer. In this
approach, the nuclei area, chromatin density, contour regularity, and nucleoli
presence, are features for nuclear pleomorphism scoring. Experimental results
showed that the proposed algorithm, with an accuracy of 86.6%, made significant
advancement in detecting cancerous nuclei compared to existing methods in the
related literature.
