There are many advanced diffusion models available for neural and body researches, while their acquisitions are different and normally difficult to be joint applied and compared in one study. In this study, we tried to calculate 7 diffusion models, including 4 neural and 3 cancer related models, using data from one acquisition, and applied it for glioma. Two diffusion acquisition strategy were evaluated, and the performance of these models in glioma grading was also compared. The result showed that both acquisition strategies could generate high quality quantitative parameters for all models, which showed significant differences between high- and low-grade tumor.
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