Morphlogical asf and k-means clustering segmentation for tumor detection

RADHAKRISHNAN, PALANIKUMAR (2015) Morphlogical asf and k-means clustering segmentation for tumor detection. In: Third International Conference on Advances in Computing, Communication and Information Technology- CCIT 2015, 26 - 27 May,2015, Birmingham B42 2SU, UNITED KINGDOM.

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Abstract

Image 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: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Morphological transformations; segmentation; edge detection; k-means clustering; tumor detection
Depositing User: Mr. John Steve
Date Deposited: 29 Apr 2019 11:44
Last Modified: 29 Apr 2019 11:44
URI: http://publications.theired.org/id/eprint/1693

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