Review On: De-Noising Medical Images by Low Rank Matrix Decomposition, NN and SVM

Volume: 3    Issue: 2

Year of Publication: 2016

Pages: (59-61)

Authors: Charankamaldeep kaur, Nishu Bansal

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Abstract

Medical imaging technology is becoming an important component of larger number of applications such as diagnosis, research and treatment. Medical images like X-Ray, MRI, PET and CT have minute to minute information about brain and whole body. So the images should be accurate and free of noise. Noise reduction plays the necessary role in medical imaging. There are various methods of noise removal like filters, wavelets and thresholding. These methods produced good results but still have some drawbacks. The limitations of the previous methods are considering and analyzing this research and the new proposed technique presents neural networks and SVM as an efficient tool for rician noise reduction. The proposed method gives more clear image with higher PSNR and improved SSIM value than the previous methods. In this paper, the techniques used for proposed work are discussed.

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Keywords

Image denoising, Rician noise PSNR,MSE, Neural Networks , SVM.