US 12,329,509 B1
High-resolution magnetic resonance fingerprinting method and device based on radio frequency encoding
Huafeng Liu, Hangzhou (CN); Dakun Hu, Hangzhou (CN); and Huihui Ye, Hangzhou (CN)
Assigned to ZHEJIANG UNIVERSITY, Hangzhou (CN)
Filed by ZHEJIANG UNIVERSITY, Hangzhou (CN)
Filed on Oct. 31, 2024, as Appl. No. 18/933,677.
Claims priority of application No. 202410350310.X (CN), filed on Mar. 26, 2024.
Int. Cl. G06K 9/00 (2022.01); A61B 5/055 (2006.01); G01R 33/50 (2006.01); G01R 33/56 (2006.01); G01R 33/561 (2006.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01)
CPC A61B 5/055 (2013.01) [G01R 33/50 (2013.01); G01R 33/5608 (2013.01); G01R 33/5614 (2013.01); G06T 7/0016 (2013.01); G06T 11/005 (2013.01); G06T 11/008 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30096 (2013.01); G06T 2210/36 (2013.01); G06T 2210/41 (2013.01)] 5 Claims
OG exemplary drawing
 
1. A high-resolution magnetic resonance fingerprinting method based on radio frequency encoding, comprising the following steps:
(1) designing and generating n magnetic resonance fingerprinting sequences with different radio frequency pulses according to required quantitative tissue parameters, wherein the tissue parameters comprise longitudinal relaxation time T1 and transverse relaxation time T2, and n is a natural number greater than 3;
wherein the magnetic resonance fingerprinting sequences are based on a 2D FISP sequence, the n magnetic resonance fingerprinting sequences differ only in the radio frequency pulses, and a corresponding excitation profile of each radio frequency pulse respectively applies a phase modulation of magnitude π to a different sub-slice, wherein a thickness of each sub-slice is 1/n of a full thickness of the corresponding excitation profile;
(2) importing the magnetic resonance fingerprinting sequences into a magnetic resonance scanner, and scanning a tissue part to be measured to obtain n sets of original k-space data;
(3) reconstructing all the k-space data to obtain a series of images; and for any pixel, solving corresponding time evolution signals of n continuous sub-slices by combining with the reconstructed n pieces of image data;
wherein the n time evolution signals of any pixel can be regarded as a weighted sum of separate time evolution signals of the n sub-slices, and the independent time evolution signals representing n continuous sub-slices can be solved by combining a weight matrix and a matrix equation determined by a radio frequency encoding method;
(4) giving a range and discretization step sizes of the required quantitative tissue parameters, and establishing a dictionary reflecting a signal evolution based on a Bloch equation; and
(5) matching all the time evolution signals of the reconstructed images from step (3) with signals in the dictionary one by one, so as to obtain a specific tissue parameter value for each pixel index, and then obtain quantitative images of the respective tissue parameters at the n sub-slices.