1 code implementation • 26 May 2022 • Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li, Zhenbang Sun, Jian Tang, Yi Xu, Bingbing Ni
This framework aims to learn multiple semantic representations for each image, and these representations are structured to encode image semantics from fine-grained to coarse-grained.
1 code implementation • 6 Apr 2022 • Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun
The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects.
2 code implementations • CVPR 2022 • Yuanfan Guo, Minghao Xu, Jiawen Li, Bingbing Ni, Xuanyu Zhu, Zhenbang Sun, Yi Xu
In this framework, a set of hierarchical prototypes are constructed and also dynamically updated to represent the hierarchical semantic structures underlying the data in the latent space.
no code implementations • 1 Jun 2021 • Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun
Method: A recently proposed deep learning-based QSM method, namely xQSM, is investigated to assess the accuracy of dipole inversion on reduced brain coverages.
1 code implementation • 14 Apr 2020 • Yang Gao, Xuanyu Zhu, Stuart Crozier, Feng Liu, Hongfu Sun
Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications.
Image and Video Processing
1 code implementation • ECCV 2018 • Xuanyu Zhu, Yi Xu, Hongteng Xu, Changjian Chen
Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years.