JOURNAL ARTICLE

Medical Image Segmentation Using Improved Mountain Clustering Approach

Abstract

This paper presents Improved Mountain Clustering (IMC) based medical image segmentation. Proposed technique is a more powerful approach for X-Ray image based diagnosing diseases like lung cancer and tuberculosis. The IMC based segmentation approach was applied on lung X-Ray images and compared with some existing techniques such as K-Means and FCM based segmentation approaches. The performance of all these segmentation approaches is compared in terms of cluster entropy as a measure of information. The segments obtained from the methods have been verified visually.

Keywords:
Image segmentation Cluster analysis Segmentation-based object categorization Segmentation Artificial intelligence Scale-space segmentation Computer science Pattern recognition (psychology) Region growing Entropy (arrow of time) Computer vision

Metrics

12
Cited By
1.24
FWCI (Field Weighted Citation Impact)
14
Refs
0.86
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Clustering Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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