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Research Article Open access CC BY 4.0

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/v9i130212

Abstract

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.

Medical images breast cancer pre-processing segmentation clustering K-means.

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