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Title |
Comparison of Segmentation based on Threshold and KCMeans Method |
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Author |
Prof. R.Spurgen Ratheash and Dr. M.Mohmed Sathik |
| Citation |
Vol. 24 No. 9 pp. 93-96 |
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Abstract |
The segmentation, detection, and extraction of infected tumour area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated many algorithm methods are available in medical imaging amongst them the Threshold technique brain tumour segmentation process gives an accurate result than other methods for MR images. The proposed method compare with the K-means clustering methods, it gives a cluster of images. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, process time and similarity of the segmented part. The experimental results achieved more accuracy, less running time and high resolution. |
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Keywords |
Threshold, k-means clustering |
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