We evaluate three different image denoising methods in cardiac diffusion tensor imaging (CDTI) regarding image quality and accuracy of parameter estimates with simulation and ex-vivo experiments. The local principal component analysis (LPCA) performs the best in improving image quality both in simulated and ex-vivo data, and the uncertainty of parameter estimations is reduced by all three algorithms in the ex-vivo experiment.
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