Abstract #3742
Support Vector Regression based Denoising for MRI Image
Di Zhao 1
1
The Dorothy M. Davis Heart & Lung Research
Institute, The Ohio State University, Columbus, Ohio,
United States
A generic problem of MRI images is the low SNR, and
filtering is the widely used technique to suppress MRI
image noise. Images filters based on machine learning
algorithms, such as Support Vector Machine (SVR), have
been shown to have superior performance because the
signal can be preserved better. In this abstract, we
apply Support Vector Regression based denoiser (SVR
denoiser) for MRI image processing.
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