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Deep Learning Super-Resolution Magnetic Resonance Imaging via Slice-Profile-Transformation Based Downsampling (UCLA Case No. 2022-062)

Summary: UCLA Researchers in the Department of Radiological Sciences have developed a deep learning-based approach for super-resolution magnetic resonance imaging. This method incorporates a novel slice-profile transformation super-resolution framework for through-plane super-resolution of multi-slice 2D MRI. This approach results in higher accuracy...

Published: 9/20/2024 | Inventor(s): Kyung Hyun Sung, Jiahao Lin

Keywords(s): Deep Learning, down sampling, High-resolution, Image Resolution, isotropic super-resolution, MRI, multiparametric MRI (mpMRI), slice-profile, Super Resolution Microscopy

Category(s): Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > MRI