DETECTION OF BRAIN TUMOR USING ENHANCED K-STRANGE POINTS CLUSTERING AND MORPHOLOGICAL FILTERING

Abstract

Image processing has become an emerging area of endless possibilities to explore and advances in this domain are gaining momentum. A brain tumor is an abnormal growth, which is caused due to cells reproducing themselves in an uncontrolled manner. In this paper, a simple and effective algorithm for detecting the presence and area of the tumor in brain MR images is described. Generally, a physician visually examines a CT or an MRI brain scan for the diagnosis of the brain tumor, which is usually a manual process. To avoid this problem, the proposed project aims to automate this problem by making use of a computer-aided method for the detection of brain tumor. This method detects brain tumor tissue with higher accuracy and lesser time as compared to the manual analysis.

Authors and Affiliations

NORA NAIK, ALAN PEREIRA, SHRUT IDHEKNE, SHUBHAM KADAM, ANKITA KALANGUTKAR

Keywords

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  • EP ID EP227543
  • DOI 10.24247/ijcseitrjun20176
  • Views 129
  • Downloads 0

How To Cite

NORA NAIK, ALAN PEREIRA, SHRUT IDHEKNE, SHUBHAM KADAM, ANKITA KALANGUTKAR (2017). DETECTION OF BRAIN TUMOR USING ENHANCED K-STRANGE POINTS CLUSTERING AND MORPHOLOGICAL FILTERING. International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), 7(3), 49-58. https://europub.co.uk/articles/-A-227543