Wanjiang Li
Sichuan University
13 Papers
3 Citations
Wanjiang Li is an academic researcher from Sichuan University. The author has contributed to research in topics: Medicine & Image quality. The author has an hindex of 1, co-authored 3 publications.
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Papers
Image quality assessment of artificial intelligence iterative reconstruction for low dose aortic CTA: A feasibility study of 70 kVp and reduced contrast medium volume.
Wanjiang Li,Yongchun You,Sihua Zhong,Tao Shuai,K. Liao,Jianqun Yu,Jin Zhao,Zhen-Lin Li,Chunyan Lu +8 more
TL;DR: In this paper , the authors investigated the image quality and feasibility of a novel artificial intelligence iterative reconstruction (AIIR) algorithm for aortic computer tomography angiography (CTA) with a low radiation dose and contrast material (CM) dosage protocol.
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CT perfusion diagnoses delayed cerebral ischemia in the early stage of the time-window after aneurysmal subarachnoid hemorrhage
TL;DR: All six CTP parameters can be used as good diagnostic tests for DCI in the early stage of the time-window according to the receiver operator characteristic (ROC) curves.
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Magnetic Resonance Imaging Markers of Cerebral Small Vessel Disease in Adults with Moyamoya Disease.
Haogeng Sun,Wanjiang Li,Chao Xia,Chao Xia,Yutao Ren,Lu Ma,Anqi Xiao,Chao You,Xiaoyu Wang,Rui Tian,Yi Liu +10 more
TL;DR: In this article, Zhao et al. used multivariate and multivariate logistic regression analysis to determine which imaging markers were independently associated with moyamoya disease (MMD) characteristics, including cerebrovascular morphology, cerebral hemodynamics, cerebroventricular events, and postoperative collateral formation (PCF).
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Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning-constrained compressed sensing.
Xin Wu,Lu Tang,Wanjiang Li,Shuai He,Xun Yue,Pengfei Peng,Tao Wu,Xiaoyong Zhang,Zhigang Wu,Yong He,Yucheng Chen,Juan Huang,Jiayu Sun +12 more
TL;DR: CSAI enables a reduction in acquisition time by 22% with superior diagnostic image quality compared with the SENSE protocol, and yielded superior image quality within a clinically feasible acquisition time in healthy participants and patients with suspected CAD.
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Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease.
Xi Wu,Li-Ping Deng,Wanjiang Li,Pengfei Peng,Xun Yue,Lu Tang,Qian Pu,Yue Ming,Xiaoyong Zhang,Xiaohua Huang,Yucheng Chen,Juan Huang,Jiayu Sun +12 more
TL;DR: In this article , the authors evaluated the diagnostic performance of coronary MR angiography with compressed sensing artificial intelligence (CSAI) in patients with suspected coronary artery disease (CAD).
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