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Here we introduced a model-based deep learning approach which enabled joint optimization of both sampling and reconstruction for CEST MRI. The main purpose is to investigate an efficient undersampling pattern for CEST acceleration. Retrospective results (4X) showed that the proposed workflow is capable of leveraging redundancy information from optimized sampling pattern, further reconstructing gold-standard-consistent contrast maps.
Liu et al. (2024) studied this question.