MORPHLOGICAL ASF AND K-MEANS CLUSTERING SEGMENTATION FOR TUMOR DETECTION

Palanikumar, Radhakrishnan (2015) MORPHLOGICAL ASF AND K-MEANS CLUSTERING SEGMENTATION FOR TUMOR DETECTION. International Journal of Advances in Image Processing Techniques, 2 (1). pp. 5-9. ISSN 2372-3998

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Abstract

mage segmentation is important feature detection in digital image processing. Identify the significant tumor presence in brain is the most worthwhile in human beings health precaution. The medical imaging, consider the pixels of particular tumor tissues for segmentation. In this paper, we propose a method to segment the tumor using k-means clustering and morphological alternative sequential filters (ASF). There are many methods proposed but our method identifies the tumor in unique manner. Brain magnetic resonance imaging (MRI) is used to segment the tumor by the combination of k-means clustering and morphological alternative sequential filters. The results are significant for identifying tumor pixels with unique segmentation process.

Item Type: Article
Subjects: Computer
Divisions: College of Computer Sciences > Computer Sciences
Depositing User: RADHA KUMAR
Date Deposited: 23 Nov 2015 12:06
Last Modified: 23 Nov 2015 12:06
URI: http://eprints.kku.edu.sa/id/eprint/148

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