Brain tissue microstructure parameters estimation method based on proximal gradient network.
10.7507/1001-5515.202004043
- Author:
Yonghong XU
1
;
Pengfei WANG
1
;
Ling DING
1
Author Information
1. Institute of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, P.R.China.
- Publication Type:Journal Article
- Keywords:
diffusion magnetic resonance;
neural network;
neurite orientation dispersion and density imaging;
tissue microstructure
- MeSH:
Brain/diagnostic imaging*;
Diffusion Magnetic Resonance Imaging;
Diffusion Tensor Imaging;
Neurites;
White Matter
- From:
Journal of Biomedical Engineering
2021;38(2):333-341
- CountryChina
- Language:Chinese
-
Abstract:
Diffusion tensor imaging technology can provide information on the white matter of the brain, which can be used to explore changes in brain tissue structure, but it lacks the specific description of the microstructure information of brain tissue. The neurite orientation dispersion and density imaging make up for its shortcomings. But in order to accurately estimate the brain microstructure, a large number of diffusion gradients are needed, and the calculation is complex and time-consuming through maximum likelihood fitting. Therefore, this paper proposes a kind of microstructure parameters estimation method based on the proximal gradient network, which further avoids the classic fitting paradigm. The method can accurately estimate the parameters while reducing the number of diffusion gradients, and achieve the purpose of imaging quality better than the neurite orientation dispersion and density imaging model and accelerated microstructure imaging via convex optimization model.
