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Mitosis Detection for Invasive Breast Cancer Grading in Histopathological Images
, D.P. Mukherjee
Published in Institute of Electrical and Electronics Engineers Inc.
PMID: 26219094
Volume: 24
Issue: 11
Pages: 4041 - 4054
Histopathological grading of cancer not only offers an insight to the patients' prognosis but also helps in making individual treatment plans. Mitosis counts in histopathological slides play a crucial role for invasive breast cancer grading using the Nottingham grading system. Pathologists perform this grading by manual examinations of a few thousand images for each patient. Hence, finding the mitotic figures from these images is a tedious job and also prone to observer variability due to variations in the appearances of the mitotic cells. We propose a fast and accurate approach for automatic mitosis detection from histopathological images. We employ area morphological scale space for cell segmentation. The scale space is constructed in a novel manner by restricting the scales with the maximization of relative-entropy between the cells and the background. This results in precise cell segmentation. The segmented cells are classified in mitotic and non-mitotic category using the random forest classifier. Experiments show at least 12% improvement in F1 score on more than 450 histopathological images at 40× magnification. © 2014 IEEE.
About the journal
JournalData powered by TypesetIEEE Transactions on Image Processing
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.