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.
Full text not available from this repository.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. © 2022 Inderscience Enterprises Ltd.. All rights reserved.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | Cited by: 2 |
| Uncontrolled Keywords: | Cells; Cytology; Diseases; Feature extraction; Medical imaging; Superpixels; eosin; hematoxylin; Background analysis; Blob analysis; Breast Cancer; Breast carcinomas; Cell detection; Mitotic activity; Mitotic cells; Super pixels; Superpixel segmentations; Whole slide images; Article; breast carcinoma; cell separation; cell shape; controlled study; feature extraction; histogram; human; human cell; human tissue; image segmentation; immunohistochemistry; measurement accuracy; mitosis; Grading |
| Subjects: | R Medicine R Medicine > RB Pathology |
| Divisions: | Faculty of Medicine Faculty of Medicine > Pathology Department |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 18 Nov 2024 03:38 |
| Last Modified: | 18 Nov 2024 03:38 |
| URI: | http://eprints.um.edu.my/id/eprint/43848 |
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