Title: Mitotic cells detection in H&E-stained breast carcinoma images

Authors: Afiqah Abu Samah; Mohammad Faizal Ahmad Fauzi; See Yee Khor; Jenny Tung Hiong Lee; Kean Hooi Teoh; Lai Meng Looi; Sarina Mansor

Addresses: Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia ' Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia ' Department of Pathology (Anatomic Pathology), Queen Elizabeth Hospital, Kota Kinabalu, Sabah, Malaysia ' Department of Pathology (Anatomic Pathology), Sarawak General Hospital, Kuching, Sarawak, Malaysia ' Department of Pathology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia ' Department of Pathology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia ' Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia

Abstract: Breast cancer is the most common cancer occurring in women, and is the second leading cause of cancer related deaths in women. Grading of breast cancer is carried out based on characteristics such as the gland formation, nuclear features, and mitotic activities, all of which need to be correctly detected first. In this paper, we proposed a system to detect mitotic cells from H&E-stained whole-slide images of breast carcinoma. The system consists of three stages, namely superpixel segmentation to group similar pixels into superpixel regions, blob analysis to separate the cells from the tissues and the background, and shape analysis and classification to distinguish mitotic cells from non-mitotic cells. The proposed system, with the histogram of oriented gradients (HOGs) and Fourier descriptor (FD) as features, is able to detect mitotic cells reliably, with more than 90% true positive rate, true negative rate and overall accuracy.

Keywords: breast carcinoma; mitosis detection; superpixel segmentation; digital pathology.

DOI: 10.1504/IJBET.2022.125102

International Journal of Biomedical Engineering and Technology, 2022 Vol.40 No.1, pp.54 - 69

Received: 18 Jul 2019
Accepted: 04 Dec 2019

Published online: 30 Aug 2022 *

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