Xinzhi Teng

685 total citations
41 papers, 356 citations indexed

About

Xinzhi Teng is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, Xinzhi Teng has authored 41 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Pulmonary and Respiratory Medicine and 11 papers in Radiation. Recurrent topics in Xinzhi Teng's work include Radiomics and Machine Learning in Medical Imaging (26 papers), Advanced Radiotherapy Techniques (11 papers) and MRI in cancer diagnosis (8 papers). Xinzhi Teng is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (26 papers), Advanced Radiotherapy Techniques (11 papers) and MRI in cancer diagnosis (8 papers). Xinzhi Teng collaborates with scholars based in Hong Kong, China and United States. Xinzhi Teng's co-authors include Jing Cai, Jiang Zhang, Saikit Lam, Haonan Xiao, Ge Ren, Chenyang Liu, Zongrui Ma, Kwok‐Hung Au, Wen Li and Bing Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Xinzhi Teng

32 papers receiving 355 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xinzhi Teng Hong Kong 12 281 98 78 76 49 41 356
Haonan Xiao Hong Kong 11 227 0.8× 61 0.6× 93 1.2× 70 0.9× 41 0.8× 23 302
Reza Reiazi Iran 13 298 1.1× 97 1.0× 43 0.6× 83 1.1× 111 2.3× 36 399
Yushi Chang United States 12 265 0.9× 103 1.1× 108 1.4× 87 1.1× 48 1.0× 21 316
Rita Simões Netherlands 10 223 0.8× 87 0.9× 52 0.7× 60 0.8× 38 0.8× 30 309
Silvia Strolin Italy 9 218 0.8× 129 1.3× 118 1.5× 64 0.8× 31 0.6× 29 362
Jordan Wong Canada 8 204 0.7× 93 0.9× 184 2.4× 77 1.0× 47 1.0× 19 339
Tanja Schimek‐Jasch Germany 16 261 0.9× 189 1.9× 108 1.4× 41 0.5× 24 0.5× 27 430
Weigang Hu China 9 262 0.9× 88 0.9× 192 2.5× 87 1.1× 40 0.8× 30 369
Sharif Elguindi United States 8 240 0.9× 99 1.0× 210 2.7× 90 1.2× 59 1.2× 17 355
Yunfeng Cui United States 13 314 1.1× 130 1.3× 227 2.9× 102 1.3× 41 0.8× 47 487

Countries citing papers authored by Xinzhi Teng

Since Specialization
Citations

This map shows the geographic impact of Xinzhi Teng'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 Xinzhi Teng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinzhi Teng more than expected).

Fields of papers citing papers by Xinzhi Teng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xinzhi Teng. 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 Xinzhi Teng. The network helps show where Xinzhi Teng may publish in the future.

Co-authorship network of co-authors of Xinzhi Teng

This figure shows the co-authorship network connecting the top 25 collaborators of Xinzhi Teng. A scholar is included among the top collaborators of Xinzhi Teng 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 Xinzhi Teng. Xinzhi Teng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Teng, Xinzhi, Jiang Zhang, Xinyu Zhang, et al.. (2025). Tumor Imaging Heterogeneity Index-Inspired Insights into the Unveiling Tumor Microenvironment of Breast Cancer. International Journal of Molecular Sciences. 26(23). 11624–11624.
2.
3.
Chen, Zhi, Yuhua Huang, Xinzhi Teng, et al.. (2025). Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy. Physics in Medicine and Biology. 70(4). 45019–45019.
4.
Guo, Wei, Bing Li, Jiang Zhang, et al.. (2024). Multi-omics and Multi-VOIs to predict esophageal fistula in esophageal cancer patients treated with radiotherapy. Journal of Cancer Research and Clinical Oncology. 150(2). 39–39. 3 indexed citations
5.
Lam, Saikit, Victor C. W. Tam, Xinzhi Teng, et al.. (2024). A multi-center, multi-organ, multi-omic prediction model for treatment-induced severe oral mucositis in nasopharyngeal carcinoma. La radiologia medica. 130(2). 161–178. 1 indexed citations
6.
Teng, Xinzhi, et al.. (2024). Enhancing the Clinical Utility of Radiomics: Addressing the Challenges of Repeatability and Reproducibility in CT and MRI. Diagnostics. 14(16). 1835–1835. 8 indexed citations
7.
8.
Zhang, Jiang, S. H. Lau, Wei Wang, et al.. (2024). Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST). SHILAP Revista de lepidopterología. 6(2). 100448–100448. 3 indexed citations
9.
Chen, Zhi, Yuhua Huang, Xinzhi Teng, et al.. (2024). Deep learning-based bronchial tree-guided semi-automatic segmentation of pulmonary segments in computed tomography images. Quantitative Imaging in Medicine and Surgery. 14(2). 1636–1651. 4 indexed citations
10.
11.
Zheng, Xiaoli, Wei Guo, Yunhan Wang, et al.. (2023). Multi-omics to predict acute radiation esophagitis in patients with lung cancer treated with intensity-modulated radiation therapy. European journal of medical research. 28(1). 126–126. 22 indexed citations
12.
Zhang, Jiang, Saikit Lam, Xinzhi Teng, et al.. (2023). Radiomic feature repeatability and its impact on prognostic model generalizability: A multi-institutional study on nasopharyngeal carcinoma patients. Radiotherapy and Oncology. 183. 109578–109578. 16 indexed citations
13.
Teng, Xinzhi, Jiang Zhang, Jiachen Sun, et al.. (2023). Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma. La radiologia medica. 128(7). 828–838. 13 indexed citations
14.
15.
Zhang, Jiang, Xinzhi Teng, Saikit Lam, et al.. (2022). Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients. Cancers. 15(1). 230–230. 5 indexed citations
16.
Ren, Ge, Xinzhi Teng, Kang Li, et al.. (2022). Artificial intelligence-assisted multistrategy image enhancement of chest X-rays for COVID-19 classification. Quantitative Imaging in Medicine and Surgery. 13(1). 394–416. 5 indexed citations
17.
Li, Bing, Ge Ren, Wei Guo, et al.. (2022). Function-Wise Dual-Omics analysis for radiation pneumonitis prediction in lung cancer patients. Frontiers in Pharmacology. 13. 971849–971849. 18 indexed citations
18.
Teng, Xinzhi, Jiang Zhang, Alex Zwanenburg, et al.. (2022). Building reliable radiomic models using image perturbation. Scientific Reports. 12(1). 10035–10035. 23 indexed citations
19.
Teng, Xinzhi, Jiang Zhang, Zongrui Ma, et al.. (2022). Improving radiomic model reliability using robust features from perturbations for head-and-neck carcinoma. Frontiers in Oncology. 12. 974467–974467. 22 indexed citations
20.
Teng, Xinzhi, et al.. (2020). Respiratory deformation registration in 4D-CT/cone beam CT using deep learning. Quantitative Imaging in Medicine and Surgery. 11(2). 737–748. 16 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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