Chenwei Li
8 Papers
Chenwei Li is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 1, co-authored 3 publications.
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Papers
Deep learning-assisted PET imaging achieves fast scan/low-dose examination
Yan Xing,Wenli Qiao,Taisong Wang,Ying Wang,Chenwei Li,Yang Lv,Chen Xi,Shu Liao,Zheng Qian,Jinhua Zhao +9 more
TL;DR: In this article , the authors investigated the impact of a deep learning (DL)-based denoising method on the image quality and lesion detectability of 18F-FDG positron emission tomography (PET) images.
Ultralow-Dose Pediatric Total-Body PET/CT Imaging Using an Artificial Intelligence Technique
Qiyang Zhang,Zizheng Xiao,Xu Zhang,Ying Ying Hu,Yu-Mo Zhao,Jingyi Wang,Jiatai Feng,Chenwei Li,Yun Zhou,Yongfeng Yang,Xin Liu,Hairong Zheng,Wei Fan,Dong Liang,Zhanli Hu +14 more
TL;DR: The proposed artificial intelligence technology is safe and can effectively enhance the quality of pediatric total-body PET/CT ultralow-dose images and has the potential to further reduce the concentration of injected tracers for clinical applications.
•Posted Content
High temporal resolution total-body dynamic PET/CT imaging based on third-order Hermite interpolation
Zixiang Chen,Yaping Wu,Na Zhang,Yu Shen,Chenwei Li,Yang Yongfeng,Xin Liu,Hairong Zheng,Dong Liang,Meiyun Wang,Hu Zhanli +10 more
TL;DR: In this paper, the authors proposed a pitch-in method for denoising images with short frame durations via pixel-level time-activity curve (TAC) correction based on third-order Hermite interpolation (Pitch-In).
Valuable Characteristic of Patlak Parametric Imaging Based on Total-Body Dynamic PET Imaging: Higher Contrast For Tumor Lesions With Respect To Hypermetabolic Tissues
Zixiang Chen,Yanhua Duan,Chenwei Li,Ying Wang,Yang Yongfeng,Xin Liu,Dong Liang,Hairong Zheng,Zhaoping Cheng,Hu Zhanli +9 more
- 23 Jul 2021
TL;DR: Patlak parametric imaging provides the valuable characteristic of higher contrast for tumor lesions than hypermetabolic tissues, which helps in the clinical detection and diagnosis of tumor tissues.
An iterative image-based inter-frame motion compensation method for dynamic brain PET imaging
Tao Sun,Yaping Wu,Yan Bai,Zhen Wang,C. Shen,Wei Dong Wang,Chenwei Li,Zhanli Hu,Dong Liang,Xin Liu,Hairong Zheng,Yongfeng Yang,Meiyun Wang +12 more
TL;DR: The synthesized phantom study showed that the proposed image-based inter-frame motion compensation approach can compensate for the simulated motion in scans with 18F-FDG, 18f-Fallypride and18F-AV45, hence facilitating the applications of dynamic PET in clinics and research.