Zhanli Hu

2.8k total citations
169 papers, 1.9k citations indexed

About

Zhanli Hu is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Radiation. According to data from OpenAlex, Zhanli Hu has authored 169 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 138 papers in Radiology, Nuclear Medicine and Imaging, 68 papers in Biomedical Engineering and 41 papers in Radiation. Recurrent topics in Zhanli Hu's work include Medical Imaging Techniques and Applications (123 papers), Advanced X-ray and CT Imaging (65 papers) and Radiomics and Machine Learning in Medical Imaging (50 papers). Zhanli Hu is often cited by papers focused on Medical Imaging Techniques and Applications (123 papers), Advanced X-ray and CT Imaging (65 papers) and Radiomics and Machine Learning in Medical Imaging (50 papers). Zhanli Hu collaborates with scholars based in China, United States and Hong Kong. Zhanli Hu's co-authors include Hairong Zheng, Yongfeng Yang, Dong Liang, Xin Liu, Dong Liang, Na Zhang, Changhui Jiang, Yongshuai Ge, Zhenxing Huang and Ziru Sang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Zhanli Hu

152 papers receiving 1.9k citations

Peers

Zhanli Hu

RNMI

RADIA

CVPR

AMPO

Kuang Gong United States

Jovan G. Brankov United States

Tobias Lasser Germany

Gene Gindi United States

Samuel Matej United States

Kerstin Hammernik Germany

Dong Liang China

Liyuan Chen China

Huafeng Liu China

Kuang Gong United States

Zhanli Hu

1.5k ×1.0

RNMI

580 ×0.8

432 ×0.8

RADIA

363 ×1.0

CVPR

92 ×0.6

AMPO

Citations per year, relative to Zhanli Hu Zhanli Hu (= 1×) peers Kuang Gong

Countries citing papers authored by Zhanli Hu

Since Specialization

Citations

This map shows the geographic impact of Zhanli Hu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhanli Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhanli Hu more than expected).

Fields of papers citing papers by Zhanli Hu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhanli Hu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhanli Hu. The network helps show where Zhanli Hu may publish in the future.

Co-authorship network of co-authors of Zhanli Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhanli Hu. A scholar is included among the top collaborators of Zhanli Hu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhanli Hu. Zhanli Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Zhang, Mengfan, et al.. (2025). Learning neural implicit surfaces from sonar image based on signed distance functions combined with occupancy representation. Expert Systems with Applications. 270. 126505–126505. 1 indexed citations

Chen, Qi, et al.. (2025). MMR-Mamba: Multi-modal MRI reconstruction with Mamba and spatial-frequency information fusion. Medical Image Analysis. 102. 103549–103549. 5 indexed citations

Feng, Rui, et al.. (2025). Natural flavonoids as highly efficient catalyst for rapid H2 generation from NaBH4 methanolysis in cold climates. Journal of environmental chemical engineering. 13(2). 115904–115904. 4 indexed citations

Kuang, Zhonghua, Ling Zhang, Ning Ren, et al.. (2025). Effects of inter-crystal scattering events on the performance of SIAT aPET. Physics in Medicine and Biology. 70(17). 17NT01–17NT01. 1 indexed citations

Fu, Minghan, et al.. (2024). SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis. Artificial Intelligence in Medicine. 157. 102972–102972. 7 indexed citations

Zhang, Qiyang, Yingying Hu, Chao Zhou, et al.. (2024). Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology. EJNMMI Physics. 11(1). 1–1. 9 indexed citations

Li, Wenbo, Zhenxing Huang, Zixiang Chen, et al.. (2024). Bidirectional dynamic frame prediction network for total-body [68Ga]Ga-PSMA-11 and [68Ga]Ga-FAPI-04 PET images. EJNMMI Physics. 11(1). 92–92.

Chen, Zixiang, Zhenxing Huang, Na Zhang, et al.. (2024). Building a Kinetic Induced Voxel-Clustering Filter (KVCF) for Low-Dose Perfusion CT Imaging. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(7). 762–773.

Niu, Ming, Zhonghua Kuang, Ning Ren, et al.. (2024). Comparison of Timing Measurement Methods of Dual-Ended Readout Scintillator Array PET Detectors. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(6). 607–617. 4 indexed citations

10.

Liu, Jiamin, Ning Ren, Zhonghua Kuang, et al.. (2024). The Software System of a Dedicated Brain PET Scanner Using Dual-Ended Readout Detectors With High-DOI Resolution. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(6). 655–663. 3 indexed citations

11.

Huang, Zhenxing, Na Zhang, Yaping Wu, et al.. (2024). Accurate Whole-Brain Segmentation for Bimodal PET/MR Images via a Cross-Attention Mechanism. IEEE Transactions on Radiation and Plasma Medical Sciences. 9(1). 47–56. 5 indexed citations

12.

Jiang, Han, et al.. (2024). Deep-Learning-Based Cross-Modality Striatum Segmentation for Dopamine Transporter SPECT in Parkinson’s Disease. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(7). 752–761. 3 indexed citations

13.

Huang, Zhenxing, Si Tang, Yingying Hu, et al.. (2024). MMCA-NET: A Multimodal Cross Attention Transformer Network for Nasopharyngeal Carcinoma Tumor Segmentation Based on a Total-Body PET/CT System. IEEE Journal of Biomedical and Health Informatics. 28(9). 5447–5458. 8 indexed citations

14.

Huang, Zhenxing, Yaping Wu, Yun Dong, et al.. (2024). Accurate Whole-Brain Image Enhancement for Low-Dose Integrated PET/MR Imaging Through Spatial Brain Transformation. IEEE Journal of Biomedical and Health Informatics. 28(9). 5280–5289. 2 indexed citations

15.

Huang, Zhenxing, Han Liu, Yaping Wu, et al.. (2023). Automatic brain structure segmentation for 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance images via deep learning. Quantitative Imaging in Medicine and Surgery. 13(7). 4447–4462. 11 indexed citations

16.

Huang, Zhenxing, Wenbo Li, Yaping Wu, et al.. (2023). Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning. European Journal of Nuclear Medicine and Molecular Imaging. 51(1). 27–39. 15 indexed citations

17.

Chen, Zixiang, Na Zhang, Qiyang Zhang, et al.. (2023). Low-dose dynamic cerebral perfusion CT reconstruction based on voxel-level TAC correction (VTC). Biomedical Signal Processing and Control. 86. 105225–105225. 2 indexed citations

18.

Chen, Zixiang, Zhaoping Cheng, Yanhua Duan, et al.. (2022). Accurate total‐body K_i parametric imaging with shortened dynamic ¹⁸F‐FDG PET scan durations via effective data processing. Medical Physics. 50(4). 2121–2134. 6 indexed citations

19.

Huang, Zhenxing, Zhou Liu, Yuanyuan Lei, et al.. (2022). Segmentation-guided Denoising Network for Low-dose CT Imaging. Computer Methods and Programs in Biomedicine. 227. 107199–107199. 14 indexed citations

20.

Pang, Zhi‐Feng, Lan Zhang, Yanru Zhou, et al.. (2022). Adaptive weighted curvature-based active contour for ultrasonic and 3T/5T MR image segmentation. Signal Processing. 205. 108881–108881. 20 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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