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

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 det...

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Main Authors: Samah, Afiqah Abu, Fauzi, Mohammad Faizal Ahmad, Khor, See Yee, Lee, Jenny Tung Hiong, Teoh, Kean Hooi, Looi, Lai Meng, Mansor, Sarina
Format: Article
Published: Inderscience Publishers 2022
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Online Access:http://eprints.um.edu.my/43848/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139004819&doi=10.1504%2fijbet.2022.125102&partnerID=40&md5=87090db13b519c57191c06cfe33e7815
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Institution: Universiti Malaya
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spelling my.um.eprints.438482024-11-18T03:38:45Z http://eprints.um.edu.my/43848/ Mitotic cells detection in H&E-stained breast carcinoma images Samah, Afiqah Abu Fauzi, Mohammad Faizal Ahmad Khor, See Yee Lee, Jenny Tung Hiong Teoh, Kean Hooi Looi, Lai Meng Mansor, Sarina R Medicine RB Pathology 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. © 2022 Inderscience Enterprises Ltd.. All rights reserved. Inderscience Publishers 2022 Article PeerReviewed Samah, Afiqah Abu and Fauzi, Mohammad Faizal Ahmad and Khor, See Yee and Lee, Jenny Tung Hiong and Teoh, Kean Hooi and Looi, Lai Meng and Mansor, Sarina (2022) Mitotic cells detection in H&E-stained breast carcinoma images. International Journal of Biomedical Engineering and Technology, 40 (1). 54 – 69. ISSN 17526418, DOI https://doi.org/10.1504/ijbet.2022.125102 <https://doi.org/10.1504/ijbet.2022.125102>. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139004819&doi=10.1504%2fijbet.2022.125102&partnerID=40&md5=87090db13b519c57191c06cfe33e7815 10.1504/ijbet.2022.125102
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic R Medicine
RB Pathology
spellingShingle R Medicine
RB Pathology
Samah, Afiqah Abu
Fauzi, Mohammad Faizal Ahmad
Khor, See Yee
Lee, Jenny Tung Hiong
Teoh, Kean Hooi
Looi, Lai Meng
Mansor, Sarina
Mitotic cells detection in H&E-stained breast carcinoma images
description 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. © 2022 Inderscience Enterprises Ltd.. All rights reserved.
format Article
author Samah, Afiqah Abu
Fauzi, Mohammad Faizal Ahmad
Khor, See Yee
Lee, Jenny Tung Hiong
Teoh, Kean Hooi
Looi, Lai Meng
Mansor, Sarina
author_facet Samah, Afiqah Abu
Fauzi, Mohammad Faizal Ahmad
Khor, See Yee
Lee, Jenny Tung Hiong
Teoh, Kean Hooi
Looi, Lai Meng
Mansor, Sarina
author_sort Samah, Afiqah Abu
title Mitotic cells detection in H&E-stained breast carcinoma images
title_short Mitotic cells detection in H&E-stained breast carcinoma images
title_full Mitotic cells detection in H&E-stained breast carcinoma images
title_fullStr Mitotic cells detection in H&E-stained breast carcinoma images
title_full_unstemmed Mitotic cells detection in H&E-stained breast carcinoma images
title_sort mitotic cells detection in h&e-stained breast carcinoma images
publisher Inderscience Publishers
publishDate 2022
url http://eprints.um.edu.my/43848/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139004819&doi=10.1504%2fijbet.2022.125102&partnerID=40&md5=87090db13b519c57191c06cfe33e7815
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