JOURNAL ARTICLE

Medical Image Segmentation Using Improved Mountain Clustering Technique Version-2

Abstract

This paper proposes Improved Mountain Clustering version-2 (IMC-2) based medical image segmentation. The proposed technique is a more powerful approach for medical image based diagnosing diseases like brain tumor, tooth decay, lung cancer, tuberculosis etc. The IMC-2 based medical image segmentation approach has been applied on various categories of images including MRI images, dental X-rays, chest X-rays and compared with some widely used segmentation techniques such as K-means, FCM and EM as well as with IMC-1. The performance of all these segmentation approaches is compared on widely accepted validation measure, Global Silhouette Index. Also, the segments obtained from the above mentioned segmentation approaches have been visually evaluated.

Keywords:
Artificial intelligence Segmentation Image segmentation Cluster analysis Computer science Segmentation-based object categorization Computer vision Scale-space segmentation Pattern recognition (psychology) Medical imaging Image (mathematics) Region growing

Metrics

11
Cited By
1.60
FWCI (Field Weighted Citation Impact)
14
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Artificial Intelligence in Healthcare
Health Sciences →  Health Professions →  Health Information Management
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