no code implementations • 10 Aug 2023 • Yanteng Zhang, Qizhi Teng, Xiaohai He, Tong Niu, Lipei Zhang, Yan Liu, Chao Ren
Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing the morphological changes and glucose metabolism changes in the brain respectively.
no code implementations • 31 Jul 2023 • Yanteng Zhanga, Xiaohai He, Yi Hao Chan, Qizhi Teng, Jagath C. Rajapakse
In this study, we demonstrate how brain networks can be created from sMRI or PET images and be used in a population graph framework that can combine phenotypic information with imaging features of these brain networks.
1 code implementation • 25 Apr 2023 • Zhenchuan Ma, Xiaohai He, Pengcheng Yan, Fan Zhang, Qizhi Teng
The proposed algorithm is flexible and can complete training and reconstruction in a short time with only one two-dimensional image.
no code implementations • 16 May 2022 • Pengcheng Yan, Qizhi Teng, Xiaohai He, Zhenchuan Ma, Ningning Zhang
Digital modeling of the microstructure is important for studying the physical and transport properties of porous media.
no code implementations • 4 Apr 2019 • Junxi Feng, Xiaohai He, Qizhi Teng, Chao Ren, Honggang Chen, Yang Li
To overcome this shortcoming, in this study we proposed a deep learning-based framework for reconstructing full image from its much smaller sub-area(s).
no code implementations • 24 Jun 2018 • Yu-Kai Wang, Qizhi Teng, Xiaohai He, Junxi Feng, Tingrong Zhang
Super resolution (SR) methods based on deep learning have achieved surprising performance in two-dimensional (2D) images.
no code implementations • 19 Sep 2017 • Honggang Chen, Xiaohai He, Chao Ren, Linbo Qing, Qizhi Teng
Experiments on compressed images produced by JPEG (we take the JPEG as an example in this paper) demonstrate that the proposed CISRDCNN yields state-of-the-art SR performance on commonly used test images and imagesets.