	US 12,232,860 B2
	Method and system for high-resolution multi-parametric quantitative magnetic resonance imaging
Shuhui Cai, Fujian (CN); Wenhua Geng, Fujian (CN); Qizhi Yang, Fujian (CN); Congbo Cai, Fujian (CN); and Zhong Chen, Fujian (CN)
Assigned to Xiamen University, Fujian (CN)
Filed by Xiamen University, Fujian (CN)
Filed on May 31, 2023, as Appl. No. 18/203,712.
Claims priority of application No. 202211618584.X (CN), filed on Dec. 15, 2022.
Prior Publication US 2024/0197196 A1, Jun. 20, 2024
Int. Cl. A61B 5/055 (2006.01); G06T 5/10 (2006.01); G06T 7/00 (2017.01); G06V 10/82 (2022.01)

CPC A61B 5/055 (2013.01) [G06T 5/10 (2013.01); G06T 7/0012 (2013.01); G06V 10/82 (2022.01); G06T 2207/10088 (2013.01)]

6 Claims

1. A method for fast high-resolution multi-parametric quantitative magnetic resonance imaging, comprising:

designing a fast high-resolution multiple overlapping-echo imaging pulse sequence;

determining sampling parameters of the fast high-resolution multiple overlapping-echo imaging pulse sequence;

constructing a deep neural network for reconstructing high-resolution multi-parametric quantitative magnetic resonance images;

generating training samples of the deep neural network;

using the training samples to train the deep neural network to obtain trained deep neural networks;

scanning a real imaging object using the fast high-resolution multiple overlapping-echo imaging pulse sequence under the sampling parameters to obtain first k-space data of the real imaging object;

pre-processing the first k-space data of the real imaging object to obtain image domain data of the real imaging object; and

inputting the image domain data of the real imaging object into the trained deep neural networks to obtain high-resolution multi-parametric quantitative magnetic resonance images of the real imaging object, wherein:

the fast high-resolution multiple overlapping-echo imaging pulse sequence comprises a signal excitation module and a data acquisition module,

the signal excitation module comprises N radio frequency (RF) excitation pulses with first time intervals (t_n) and flip angles (α_n), slice selection gradients (G_ss) corresponding to the N RF excitation pulses, and echo shift gradients (G_n),

n=1, 2, . . . , N, and N≥2,

each of the N RF excitation pulses is combined with a corresponding one of the slice selection gradients (G_ss) in a slice selection dimension for slice selection,

the echo shift gradients (G_n) are applied after a corresponding RF excitation pulse of the N RF excitation pulses along a frequency encoding dimension and a phase encoding dimension,

the data acquisition module comprises a pre-phase gradient (G_pre), M refocusing pulses with second time intervals (ESP) and flip angles (β_m), crushing gradients (G_cr), phase encoding gradients (G_pe,i,m), frequency encoding gradients (G_ro), and dephase encoding gradients (G_pe,i,m′),

i represents an ith scanning,

m=1, 2, . . . , M, and M≥2,

the pre-phase gradient (G_pre) is applied along the frequency encoding dimension, and a size of the pre-phase gradient (G_pre) is half of a corresponding one of the frequency encoding gradients (G_ro),

the crushing gradients (G_cr) are applied before and after each refocusing pulse of the M refocusing pulses, and sizes and directions of the crushing gradients (G_cr) along the frequency encoding dimension, the phase encoding dimension, and the slice selection dimension are the same, and

the phase encoding gradients (G_pe,i,m), the frequency encoding gradients (G_ro), and the dephase encoding gradients (G_pe,i,m′) are applied after each refocusing pulse of the M refocusing pulses, and the phase encoding gradients (G_pe,i,m) and the dephase encoding gradients (G_pe,i,m′) have same sizes but opposite directions.