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Proceedings Paper

Deep detection and classification of mitotic figures
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Paper Abstract

Breast cancer is the second largest cause of cancer death among women after skin cancer. Mitotic count is an important biomarker for predicting the breast cancer prognosis according to Nottingham Grading System. Pathologists look for tumour areas and select 10 HPF(high power field) images and assign a grade based on the number of mitotic counts. Mitosis detection is a tedious task because the pathologist has to inspect a larger area. The pathologist’s views about mitotic cell are also subjective. Because of these problems, an assisting tool for the pathologist will generalize and reduce the time for diagnosis. Due to recent advancements in whole slide imaging, CAD(computer-aided diagnosis) systems are becoming popular. Mitosis detection for scanner images is difficult because of variability in shape, color, texture and its similar appearance to apoptotic nuclei, darkly stained nuclei structures. In this paper, the mitotic detection task is carried out with state of the art object detector (Faster R-CNN) and classifiers (Resnet152, Densenet169, and Densenet201) for ICPR 2012 dataset. The Faster R-CNN is used in two ways. In first, it was treated as an object detector which gave an F1-score of 0.79 while in second, it was treated as a Region Proposal Network followed by an ensemble of classifiers giving an F1-score 0.75.

Paper Details

Date Published: 18 March 2019
PDF: 6 pages
Proc. SPIE 10956, Medical Imaging 2019: Digital Pathology, 109560T (18 March 2019); doi: 10.1117/12.2508770
Show Author Affiliations
Balamurali Murugesan, Indian Institute of Technology Madras (India)
Healthcare Technology Innovation Ctr. (India)
Sakthivel Selvaraj, Healthcare Technology Innovation Ctr. (India)
Kaushik Sarveswaran, Healthcare Technology Innovation Ctr. (India)
Keerthi Ram, Healthcare Technology Innovation Ctr. (India)
Jayaraj Joseph, Healthcare Technology Innovation Ctr. (India)
Mohanasankar Sivaprakasam, Indian Institute of Technology Madras (India)
Healthcare Technology Innovation Ctr. (India)

Published in SPIE Proceedings Vol. 10956:
Medical Imaging 2019: Digital Pathology
John E. Tomaszewski; Aaron D. Ward, Editor(s)

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