Automatic Spinal Cord Segmentation From Medical MR Images using Hybrid Algorithms

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Dr. R. Priya, M. Umaibanu

Abstract

Medical image processing is the top most research area. There are huge amount of researches found in the medical image analyze, classification and segmentation process. Spinal cord segmentation of MRI images is the challenging process. In the proposed research work, automatic Spinal Cord (SC) segmentation from medical MRI image is performed with various techniques. The proposed work improves the segmentation with less iteration and improved accuracy by adopting improved Weighted Expectation Maximization (WEM) and Strong Fitness Firefly (SFF) algorithms. The proposed work effectively segments the spinal cord by applying effective pre-processing, image enhancement process and clustering with less iterations. Using the combination of different techniques, the proposed system effectively identifies the spinal cord from the MRI image, the experiments performed using Matlab tool. The accuracy is calculated and shown for the proposed system. The result shows, the mixed approach of WEM and SFF increases the segmentation accuracy than using the WEM alone.

Article Details

How to Cite
, D. R. P. M. U. (2017). Automatic Spinal Cord Segmentation From Medical MR Images using Hybrid Algorithms. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 3(12), 226–230. Retrieved from http://www.ijfrcsce.org/index.php/ijfrcsce/article/view/398
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