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Vol. 1 No. 2 (2020)

Articles

Region of Interest Segmentation Based on Clustering Techniques for Breast Cancer Ultrasound Images: A Review

https://doi.org/10.38094/jastt20201328

Published 2020-06-24

  • Muhammad Muhammad
    • ,
  • Diyar Zeebaree
    • ,
  • Adnan Mohsin Abdulazeez Brifcani
    • ,
  • Jwan Saeed
    • ,
  • Dilovan Asaad Zebari

Muhammad Muhammad
Information Security Department. Technical Informatics College of Akre, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Diyar Zeebaree
Research Center of Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Adnan Mohsin Abdulazeez Brifcani
Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Jwan Saeed
IT Department. Duhok Technical Institute, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Dilovan Asaad Zebari
Research Center of Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq

Abstract

The most prevalent cancer amongst women is woman breast cancer. Ultrasound imaging is a widely employed method for identifying and diagnosing breast abnormalities. Computer-aided diagnosis technologies have lately been developed with ultrasound images to help radiologists enhance the accuracy of the diagnosis. This paper presents several ultrasound image segmentation techniques, mainly focus on eight clustering methods over the last 10 years, and it shows the advantages and disadvantages of these approaches. Breast ultrasound image segmentation is, therefore, still an accessible and challenging issue due to numerous ultrasound artifacts introduced in the imaging process, including high speckle noise, poor contrast, blurry edges, weak signal-to-noise ratio, and intensity inhomogeneity.

Keywords

Breast cancer, Computer-aided diagnosis, Ultrasound image, Segmentation, Clustering

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