Image Segmentation Using K- Means Clustering Method for Brain Tumour Detection

Authors

  • S Thylashri

  • Udutha Mahesh Yadav

  • T Danush Chowdary

How to Cite

Thylashri, S., Mahesh Yadav, U., & Danush Chowdary, T. (2018). Image Segmentation Using K- Means Clustering Method for Brain Tumour Detection. International Journal of Engineering and Technology, 7(2.19), 97-100. https://doi.org/10.14419/ijet.v7i2.19.15058

Received date: July 4, 2018

Accepted date: July 4, 2018

Published date: April 17, 2018

DOI:

https://doi.org/10.14419/ijet.v7i2.19.15058

Keywords:

Segmentation, clustering, Brain tumour, k-means, Magnetic Resonance Imaging (MRI)

Abstract

Brain tumour is an irregular development by cells imitating among them in an unstoppable way. Specific identification of size and area of Brain tumour assumes a fundamental part in the analysis of tumour. Image processing is a dynamic research territory in which processing of image in medical field is an exceedingly difficult field. Segmentation of image assumes a critical part in handling of image as it helps in the finding of suspicious districts from the restorative image. In this paper a proficient algorithm is proposed for detection of tumour based on segmentation of brain by means of clustering technique. The main idea in this clustering algorithm is to transfer  a given gray-level image and then separate  tumour objects position  from other items of an MR image by using K-means clustering. Experiments say that segmentation for MR brain images can be done to help medical professionals to identify exactly size and region of the tumour located area in brain.

 

 

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How to Cite

Thylashri, S., Mahesh Yadav, U., & Danush Chowdary, T. (2018). Image Segmentation Using K- Means Clustering Method for Brain Tumour Detection. International Journal of Engineering and Technology, 7(2.19), 97-100. https://doi.org/10.14419/ijet.v7i2.19.15058

Received date: July 4, 2018

Accepted date: July 4, 2018

Published date: April 17, 2018