Publication Type:

Conference Paper

Source:

International Conference on Communications and Signal Processing (ICCSP’16), IEEE, Adhiparasakthi Engineering College, Melmaruvathur (2016)

URL:

http://ieeexplore.ieee.org/document/7754192/

Abstract:

In today's world, X-ray imaging is the low cost diagnostic technique when compared with all other medical imaging techniques. In this paper, the proposed method is to classify X-ray images based on tumor. The features are extracted using Singular Value Decomposition (SVD) and classified using different kernels in Library for Support Vector Machine (Lib-SVM) and Grand Unified Regularized Least Squares (GURLS). The proposed method is experimented on X-ray image dataset which is approved by an Oncologist. The effectiveness of proposed method is validated based on classification parameters. The experiment result analysis shows that Gaussian-ho in GURLS provides 95% classification accuracy which is 5% higher than RBF kernel in LibSVM. The performance of the proposed system is validated by an Oncologist.

Cite this Research Publication

P. A, R, M., Sowmya V., and Dr. Soman K. P., “X-ray Image Classification Based On Tumor using GURLS and LIBSVM”, in International Conference on Communications and Signal Processing (ICCSP’16), Adhiparasakthi Engineering College, Melmaruvathur , 2016.

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