Image Segmentation Using K- Means Clustering Method for Brain Tumour Detection
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2018-04-17 https://doi.org/10.14419/ijet.v7i2.19.15058
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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 & Technology, 7(2.19), 97-100. https://doi.org/10.14419/ijet.v7i2.19.15058Received date: 2018-07-04
Accepted date: 2018-07-04
Published date: 2018-04-17