MRF ZOOM:A Fast Dictionary Searching Algorithm For Magnetic Resonance Fingerprinting

Compared with the traditional quantitative imaging,magnetic resonance imaging fingerprint with high accuracy?fast imaging speed and insensitivity of movement,simultaneous multi parameter imaging and so on,but its brute-force dictionary generating and searching(DGS)process caused a huge disk space demand and the computational burden,prohibiting it from a practical multiple slice high-definition imaging.In this paper,a fast and space efficient DGS algorithm: MRF ZOOM,is proposed in this paper.Based on an empirical analysis of properties of the distance function of the acquired MRF signal and the pre-defined MRF dictionary entries,breaks the multiplicative computation complexity into an additive one and enabling a resolution scalable multi-resolution DGS process.The simulation results show that MRF ZOOM can be hundreds of times faster than the original violent DGS algorithm.Acceleration or even faster when a pre-defined MRF dictionary time is added.When the higher resolution quantization parameters are used,the correct parameter value can be found within 117 seconds for the 64 * 64 image.The speed of using MRF ZOOM is faster when the most adjacent voxel parameter is a space constraint condition.