Medical Images Breast Cancer Segmentation Based on K-Means Clustering Algorithm: A Review
Noor Salah Hassan, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dathar A. Hasan
Asian Journal of Research in Computer Science · pp. 23–38 · Published 24 May 2021
10.9734/ajrcos/2021/v9i130212Abstract
Early diagnosis is considered important for medical images of breast cancer, the rate of recovery and safety of affected women can be improved. It is also assisting doctors in their daily work by creating algorithms and software to analyze the medical images that can identify early signs of breast cancer. This review presents a comparison has been done in term of accuracy among many techniques used for detecting breast cancer in medical images. Furthermore, this work describes the imaging process, and analyze the advantages and disadvantages of the used techniques for mammography and ultrasound medical images. K-means clustering algorithm has been specifically used to analyze the medical image along with other techniques. The results of the K-means clustering algorithm are discussed and evaluated to show the capacity of this technique in the diagnosis of breast cancer and its reliability to identify a malignant from a benign tumor.
Cited by 28
Sophia Olga Pontoh, Winsy Weku, Djoni Hatidja · Operations Research: International Conference Series · 2022
Diyar Qader Zeebaree, A. Abdulazeez, Lozan M. Abdullrhman · Asian Journal of Research in Computer Science · 2021
O. S. Kareem, A. K. Al-Sulaifanie, D. Hasan · Asian Journal of Research in Computer Science · 2021
Kang Yu, Bingbing Li, Xi-Peng Pan · Biomedical Signal Processing and Control · 2026
Karim Gasmi, Ibtihel Ben Ltaifa, Moez Krichen · AIMS Mathematics · 2025
O. V. Sudakov, D. V. Dmitriev · Proceedings of the 32nd International Conference on Computer Graphics and Vision · 2022
Chengmao Wu, Wen Wu · Circuits, Systems, and Signal Processing · 2024
Adam Fahmi Khariri, Putroue Keumala Intan, Moh. Hafiyusholeh · Springer Proceedings in Mathematics & Statistics · 2024
Related research
- Reproductive Factors Associated with the Risk of Breast Cancer among Malaysian Women: A Multi-Centre Case-Control Study — shares topic coverage
- Factors Predicting the Utilization of Breast Cancer Screening Services among Women Working in a Private University in Ogun State, Nigeria — shares topic coverage
- Breast Cancer Screening Trend Year 2017 among South-Western Nigeria Female Residents — shares topic coverage
- Complementary Medicine Intervention in Breast Cancer Patients with Pain — shares topic coverage
- Breast Cancer Knowledge and Mammography Uptake among Women Aged 40 Years and Above in Calabar Municipality, Nigeria — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
28
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.