Keywords: Machine Learning/Artificial Intelligence, Parkinson's Disease, Neuromelanin, Denoising
Neuromelanin (NM) has been considered an associated biomarker of Parkinson’s disease (PD). Conventional NM visualizeing techniques requires about 5~10min which is sub-optimal for scanning PD patient with movement disorders. Recently, SandwichNM is reduced scan time to 5m 30s, but it is still may not enough.
In this research, we approach this issue in the viewpoint of image post processing with denoising techniques to reduce scan time. After 162 NM MRI data acquisition with short scan time, we demonstrated that using denoising technique can improve the distinguishability for NM segmentation.
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