Medical image segmentation using modified fuzzy c mean based clustering

Locating disease area in medical images is one of the most challenging task in the field of image segmentation. This paper presents a new approach of image-segmentation using modified fuzzy c-means(MFCM) clustering. Considering low illuminated medical images, the input image is firstly enhanced usin...

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Bibliographic Details
Main Authors: Kumar, Dharmendra, Solanki, Anil Kumar, Ahlawat, Anil, Malhotra, Sukhnandan
Format: Conference Proceeding
Language:English
Subjects:
Clustering
Equalization
Experimentation
Histograms
Image enhancement
Image segmentation
Medical imaging
Noise sensitivity
Online Access:Get full text
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Summary:Locating disease area in medical images is one of the most challenging task in the field of image segmentation. This paper presents a new approach of image-segmentation using modified fuzzy c-means(MFCM) clustering. Considering low illuminated medical images, the input image is firstly enhanced using histogram equalization(HE) technique. The enhanced image is now segmented into various regions using the MFCM based approach. The local information is employed in the objective-function of MFCM to overcome the issue of noise sensitivity. After that membership partitioning is improved by using fast membership filtering. The observed result of the proposed scheme is found suitable in terms of various evaluating parameters for experimentation.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0003548