Publication Type : Conference Paper
Publisher : International Conference on Communications and Signal Processing (ICCSP’16)
Source : International Conference on Communications and Signal Processing (ICCSP’16), IEEE, Adhiparasakthi Engineering College, Melmaruvathur (2016)
Url : http://ieeexplore.ieee.org/document/7754192/
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking, Electronics Communication and Instrumentation Forum (ECIF)
Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication
Year : 2016
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, 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.