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Abstract #1713

IVIM quantification and b-value optimization using deep neural network

Wonil Lee1, Byungjai Kim1, Jongyeon Lee1, and HyunWook Park1
1KAIST, Daejeon, Korea, Republic of

Many studies have been performed to show that IVIM could be used as a biomarker for various diseases(1-5). Since IVIM is formulated by a biexponential model, it is difficult to quantify the IVIM parameters. Researchers have tried to solve the inverse problems of the biexponential model using two approaches:improving fitting method and selecting optimized b-values(6-8). The trained DNN and the optimized b-values by the proposed method quantified IVIM parameters more accurately than combination of the conventional b-value optimization schemes with DNN fitting method. The optimized b-values by the proposed method showed superior performance even when combined with other fitting methods.

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