Sep 15, 2022 · We propose a hybrid graph transformer (HGT) to explicitly consider the q-space geometric structure with a graph neural network (GNN) and make full use of ...

Sep 15, 2022 · A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely ...

This paper proposed a deep learning approach for estimation of tissue microstructure parameters from sparse diffusion MRI data. They specifically investigate a ...

Apr 19, 2024 · A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely ...

Sep 18, 2022 · A potential remedy to this problem is by using deep learning techniques to predict high-quality diffusion microstructural indices from sparsely ...

We propose a hybrid graph transformer (HGT) to jointly consider the information in both x-space and q-space for improving the accuracy of microstructural ...

Oct 8, 2023 · We propose 3D hybrid graph transformer (3D-HGT), an advanced microstructure estimation model capable of making full use of 3D spatial information and angular ...

May 14, 2024 · Deep learning has drawn increasing attention in microstructure estimation with undersampled diffusion MRI (dMRI) data.

Jun 5, 2024 · ... Hybrid Graph. Transformer for Tissue Microstructure Estimation with Undersampled Diffusion. MRI Data. In: Wang, L., Dou, Q., Fletcher, P.T. ...

Apr 21, 2023 · Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data. In: Medical Image Computing and Computer ...