Medical Image Segmentation Approaches: A Survey

International Journal of Electronics and Communication Engineering

© 2020 by SSRG - IJECE Journal

Volume 7 Issue 7

Year of Publication : 2020

Authors : Nageswari P, Rajan S, Manivel K

10.14445/23488549/IJECE-V7I7P101

How to Cite?

Nageswari P, Rajan S, Manivel K, "Medical Image Segmentation Approaches: A Survey," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 7, pp. 1-3, 2020. Crossref, https://doi.org/10.14445/23488549/IJECE-V7I7P101

Abstract:

Segmentation is an important preprocessing step in medical image analysis. Its main aim is to partition the image areas into several regions concerning similar distinctiveness such as texture, color, and intensity. It has been widely useful in many purposes such as recognition of tumors and coronary borders, planning for surgery, measuring the tumor volume, blood cell classification, and extraction of heart image from cardiac cine angiograms. In recent years, for the medical image, many approaches have been proposed for the segmentation process. Thresholding, region-based, edge-based, and clustering-based methods are the important segmentation process techniques for medical image analysis. This paper studies the different types of segmentation approaches that have been used in medical imaging frameworks.

Keywords:

Segmentation, Medical image, Speckle noise, Fuzzy Clustering Technique.

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