Open AccessMedical Images Breast Cancer Segmentation Based on K-Means Clustering Algorithm: A Review
Author(s) -
Noor Salah Hassan,
Adnan Mohsin Abdulazeez,
Diyar Qader Zeebaree,
Dathar Abas Hasan
Publication year - 2021
Publication title -
asian journal of research in computer science
Language(s) - English
Resource type - Journals
ISSN - 2581-8260
DOI - 10.9734/ajrcos/2021/v9i130212
Subject(s) - cluster analysis , breast cancer , mammography , segmentation , computer science , reliability (semiconductor) , image segmentation , medical imaging , cancer , k means clustering , algorithm , artificial intelligence , medicine , power (physics) , physics , quantum mechanics
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.