Quantification of intravoxel incoherent motion with optimized b-values using deep neural network.

Journal: Magnetic resonance in medicine

Published Date: Feb 16, 2021

Abstract

PURPOSE: To develop a framework for quantifying intravoxel incoherent motion (IVIM) parameters, where a neural network for quantification and b-values for diffusion-weighted imaging are simultaneously optimized.

Authors

Wonil Lee

Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
Byungjai Kim

School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
HyunWook Park

Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea.

Keywords

Diffusion Magnetic Resonance Imaging Healthy Volunteers Humans Motion Neural Networks, Computer Perfusion

External Resources

View on PubMed Access via DOI PubMed (33594783)

Quantification of intravoxel incoherent motion with optimized b-values using deep neural network.

Abstract

Authors

Keywords

External Resources

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