H
Hua Li
Researcher at Shenyang Pharmaceutical University
Publications - 191
Citations - 6750
Hua Li is an academic researcher from Shenyang Pharmaceutical University. The author has contributed to research in topics: Image quality & Image segmentation. The author has an hindex of 29, co-authored 181 publications receiving 4559 citations. Previous affiliations of Hua Li include Carle Foundation Hospital & Fourth Military Medical University.
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Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods.
Canrong Wu,Yang Liu,Yueying Yang,Peng Zhang,Wu Zhong,Yali Wang,Qiqi Wang,Yang Xu,Mingxue Li,Xing-Zhou Li,Mengzhu Zheng,Lixia Chen,Hua Li,Hua Li +13 more
TL;DR: This study systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling and constructed a database of 78 commonly used anti-viral drugs.
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Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132.
TL;DR: The Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes.
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Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation.
TL;DR: An automatic classification segmentation tool for helping screening COVID-19 pneumonia using chest CT imaging and shows very encouraging performance with a dice coefficient higher than 0.88 for the segmentation and an area under the ROC curve higher than 97% for the classification.
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Automatic selection of tube potential for radiation dose reduction in CT: A general strategy
TL;DR: A general strategy to automatically select the most dose efficient tube potential for CT exams was developed that takes into account patient size and diagnostic task.
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Vessels as 4-D Curves: Global Minimal 4-D Paths to Extract 3-D Tubular Surfaces and Centerlines
Hua Li,Anthony Yezzi +1 more
TL;DR: This approach combines all of the benefits of minimal path techniques such as global minimizers, fast computation, and powerful incorporation of user input, while also having the capability to represent and detect vessel surfaces directly which so far has been a feature restricted to active contour and surface techniques.