Rapid and Efficient Medical Image Segmentation Using Thresholding and CLAHE with 3-Level FCM Clustering

Kumar, Sunil; Kumar, Dilip; Bhagat, Monu

doi:10.2139/ssrn.3574648

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Rapid and Efficient Medical Image Segmentation Using Thresholding and CLAHE with 3-Level FCM Clustering

Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019

9 Pages Posted: 15 Apr 2020

See all articles by Sunil Kumar

Monu Bhagat

NIT Jamshedpur, India

Date Written: April 13, 2020

Abstract

The segmentation of medical images is a method to examine and extract different portions of medical input data. Several ways have been devel-oped to improve the efficiency of these segmentation techniques. The main goal of the proposed method is to develop a rapid and efficient 3-level FCM cluster-ing algorithm and which is based on the 3 level threshold technique. The intro-duced method uses pseudo-random numbers generator which is normally dis-tributed for initial fuzzy estimates, so it acquires threshold faster than the regu-lar method. Before image segmentation, we use CLAHE to enhance the quality and resolution of the noise image which significantly improves segmentation performance. The proposed method evaluates performance for different expo-nential values of partitioned metrics for better segmentation.

Keywords: Segmentation of medical images, Fuzzy C-mean Clustering, Thresholdings, entropy, CLAHE

Suggested Citation: Suggested Citation

Kumar, Sunil and Kumar, Dilip and Bhagat, Monu, Rapid and Efficient Medical Image Segmentation Using Thresholding and CLAHE with 3-Level FCM Clustering (April 13, 2020). Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019, Available at SSRN: https://ssrn.com/abstract=3574648 or http://dx.doi.org/10.2139/ssrn.3574648