Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 19, Pages: 1-6
V. Viswa Priya* and Shobarani
*Author for correspondence
V. Viswa Priya
Department of CSE, Dr. MGR Educational and Research Institute University, Chennai - 600032, Tamil Nadu, India; [email protected]
Background: For effective tumor diagnosis, early brain tumor detection becomes an important procedure. Despite a huge number of tumor detection techniques available, brain tumor segmentation is still a challenging field because of the complex characteristic of the brain MR images. This work aims to achieve an efficient segmentation approach for tumor detection. Methods: The Contextual Clustering based segmentation methodology proposed here includes image pre- processing and tumor segmentation. Image pre-processing removes total noise in the image and corrects the boundaries. Tumor segmentation uses Contextual Clustering algorithm to segment the tumor part from the input MR images. Findings: An automatic method of tumor detection and localization in the brain MRI is proposed here which avoids false segmentation and improves accuracy. Application: This stated Contextual Clustering algorithm works efficiently in brain tumor segmentation for the MRI brain images and produces accurate results for the input datasets and used in medical fields.
Keywords: Brain Tumor Segmentation, Contextual Clustering, MRI (Magnetic Resonance Imaging), Medical Imaging, Tumor Detection
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