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Researchers applied temporal deep learning reconstruction using the Movienet network to accelerate chemical exchange saturation transfer magnetic resonance fingerprinting (CEST-MRF). The method was tested on data from ten healthy volunteers, showing improved reconstruction speed for radial CEST-MRF...
Researchers applied temporal deep learning reconstruction using the Movienet network to accelerate chemical exchange saturation transfer magnetic resonance fingerprinting (CEST-MRF). The method was tested on data from ten healthy volunteers, showing improved reconstruction speed for radial CEST-MRF...
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Purpose: To accelerate chemical exchange saturation transfer magnetic resonance fingerprinting (CEST-MRF) using temporal deep learning reconstruction. Methods: Ten healthy volunteers underwent repeated test-retest golden-angle radial CEST-MRF acquisitions with 30 measurements and 34 spokes per measurement. The...
Faster reconstruction of CEST-MRF data can enhance the efficiency of MRI scans, potentially improving clinical workflows and patient throughput. This approach demonstrates the utility of deep learning in accelerating complex medical imaging techniques.
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