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An Enhanced Brain Tumor Area Detection and Segmentation Techniques in MRI Medical Images using Modified K-Means Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 143 - Number 13 |
| Year of Publication: 2016 |
| Authors: Saumya Gupta, Monika Agrawal, Sanjay Kumar Sharma |
10.5120/ijca2016910254
|
Saumya Gupta, Monika Agrawal, Sanjay Kumar Sharma . An Enhanced Brain Tumor Area Detection and Segmentation Techniques in MRI Medical Images using Modified K-Means Algorithm. International Journal of Computer Applications. 143, 13 ( Jun 2016), 46-50. DOI=10.5120/ijca2016910254
Abstract
In medical image processing, one amongst the most important goal of the tumor detection. Within the human body there are different tumors deceases in now days. Brain tumor is very unsafe deceases for human body. Medical image processing provides a good solution for brain tumor detection with the help of MRI tumor image segmentation. Image segmentation refers to the method of partitioning an image into mutually exclusive regions. It may be considered as the most essential and crucial method for facilitating the delineation, characterization, and visualization of regions of interest in any medical image. Despite intensive analysis, segmentation remains a challenging issue due to the various image content, cluttered objects, occlusion, image noise, non-uniform object texture, and other factors. There are many algorithms and techniques accessible for image segmentation but still there has to develop an efficient, fast technique of medical image segmentation. This paper presents an efficient image segmentation methodology using K-means clustering technique.
References
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