Medical image segmentation using improved mountain clustering technique version-2

dc.contributor.authorVerma, N.K.
dc.contributor.authorRoy, A.
dc.contributor.authorVasikarla, S.
dc.date.accessioned2026-02-06T06:40:48Z
dc.date.issued2010
dc.description.abstractThis 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. © 2010 IEEE.
dc.identifier.citationITNG2010 - 7th International Conference on Information Technology: New Generations, 2010, Vol., , p. 156-161
dc.identifier.urihttps://doi.org/10.1109/ITNG.2010.219
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/33166
dc.subjectClustering
dc.subjectImproved
dc.subjectMedical image
dc.subjectSegmentation
dc.titleMedical image segmentation using improved mountain clustering technique version-2

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