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摘要A super-fast dictionary generation and searching algorithm was developed for parameter quantification using magnetic resonance fingerprinting(MRF).MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan.But it has a multiplicative computation complexity,resulting in a huge disk space demand and computational burden,which can easily go beyond the maximum capacity of any state-of-art computers.Based on an empirical analysis of the distance(between the MR fingerprints and dictionary items)function property,a multi-scale ZOOM like dictionary generation and searching algorithm was designed.The so-called MRF ZOOM uses a parameter separable dictionary generating and searching process to reduce the multiplicative computation complexity into additive one and uses a multi-resolution searchlight to find the parameter with specified precision.Evaluations using synthetic data showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in.MRF ZOOM provides a super-fast solution for MR parameter quantification.