An end-to-end LSTM-Attention based framework for quasi-steady-state CEST prediction

An end-to-end LSTM-Attention based framework for quasi-steady-state CEST prediction

Chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI) often takes prolonged saturation duration (Ts) and relaxation delay (Td) to reach the steady state, and yet the insufficiently long Ts and Td in actual experiments may underestimate the CEST measurement. In this study, we...

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Bibliographic Details
Main Authors: Wei Yang, Jisheng Zou, Xuan Zhang, Yaowen Chen, Hanjing Tang, Gang Xiao, Xiaolei Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Neuroscience
Subjects:
CEST-MRI
QUASS CEST
deep learning
Bloch-McConnell equation
LSTM-Attention
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1281809/full

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