Global deep learning optimization of chemical exchange saturation transfer magnetic resonance fingerprinting acquisition schedule

• Published in: NMR in biomedicine Vol. 36; no. 10; p. e4954
• Main Authors: Cohen, Ouri, Otazo, Ricardo
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.10.2023
• Subjects: Biological products; Brain - diagnostic imaging; Carcinoma, Renal Cell; Correlation coefficient; Correlation coefficients; Deep Learning; Error analysis; Fingerprinting; Humans; Image reconstruction; Imaging techniques; In vivo methods and tests; Kidney Neoplasms; Magnetic resonance; Magnetic Resonance Imaging - methods; Magnetic Resonance Spectroscopy; Mathematical analysis; Metastases; Neuroimaging; Noise reduction; Optimization; Parameters; Phantoms, Imaging; Renal cell carcinoma; Reproducibility; Reproducibility of Results; Schedules; Substantia alba; Substantia grisea; Tissues; deep learning; magnetic resonance fingerprinting (MRF); DRONE; chemical exchange saturation transfer (CEST); global optimization

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging technique but suffers from long scan times and complicated processing. CEST was recently combined with magnetic resonance fingerprinting (MRF) to address these shortcomings. However, the CEST‐MRF signal depends on mult...