Using a deep learning prior for accelerating hyperpolarized < sup > 13 < /sup > C MRSI on synthetic cancer datasets
CONCLUSION: The proposed singular value decomposition + iterative deep learning model could be considered as a general framework that extended the application of deep learning MRI reconstruction to metabolic imaging. The morphology of tumors and metabolic images could be measured robustly in six times acceleration using our method.PMID:38440832 | DOI:10.1002/mrm.30053
Source: Magnetic Resonance in Medicine - Category: Radiology Authors: Zuojun Wang Guanxiong Luo Ye Li Peng Cao Source Type: research
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