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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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