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- W4385555009 abstract "Quantitative R2* map is an important liver disease indicator. However, the availability of R2* map is limited by the long scan time. In this study, we present a new paradigm to predict R2* and B0 maps from dual echo images. A self-attention deep convolutional neural network is trained and validated, where promising accuracy has been obtained. The proposed quantitative parametric mapping approach has a potential to eliminate the necessity for additional data acquisition other than clinical routine." @default.
- W4385555009 created "2023-08-04" @default.
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- W4385555009 date "2023-08-03" @default.
- W4385555009 modified "2023-09-27" @default.
- W4385555009 title "Derivation of liver R2* and B0 maps from dual-echo MR images via deep learning" @default.
- W4385555009 doi "https://doi.org/10.58530/2022/3378" @default.
- W4385555009 hasPublicationYear "2023" @default.
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