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Abstract #1381

Accelerating whole brain vessel wall imaging of isotropic 0.4 mm3 on 5T by 10-fold using deep learning reconstruction

Sen Jia1, Jiaying Zhao2,3, Lei Zhang1, Jing Cheng1, Zhuoxu Cui2, Ye Li1, Xin Liu1, Hairong Zheng1, and Dong Liang1,2
1Paul C. Lauterbur Research Center for Biomedical lmaging, Shenzhen Institute of Advanced Technology, Shenzhen, China, 2Research Center for Medical AI, Shenzhen Institute of Advanced Technology, Shenzhen, China, 3University of Chinese Academy of Sciences, Beijing, China

Synopsis

Keywords: Vessel Wall, Atherosclerosis

Motivation: Whole brain vessel wall imaging (VWI) of isotropic 0.4 mm3 on 3T can’t utilize higher than 5-fold acceleration to reduce the scan time due to insufficient signal-to-noise.

Goal(s): To achieve 10-fold accelerated whole brain VWI of isotropic 0.4 mm3 on the 5T scanner with a 48-channel transmit receive head coil.

Approach: Deep learning (DL) reconstruction equipped with 3D convolution neural network was developed to alleviate the nonuniform noise amplified by SPIRiT reconstruction and the B1 inhomogeneity of 5T scanner.

Results: The proposed DL SPIRiT reconstruction achieves 10-fold accelerated intracranial VWI scan on 5T in 6 minutes and give better VWI quality than 3T.

Impact: This work develops a 10-fold accelerated whole brain vessel wall imaging of isotropic 0.4 mm3 in 6 minutes using deep learning (DL) unrolled SPIRiT reconstruction on the 5T scanner equipped with a 48-channel transmit receive head coil.

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Keywords