Minggang Su

685 total citations
86 papers, 441 citations indexed

About

Minggang Su is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Surgery. According to data from OpenAlex, Minggang Su has authored 86 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Pulmonary and Respiratory Medicine, 28 papers in Oncology and 21 papers in Surgery. Recurrent topics in Minggang Su's work include Medical Imaging Techniques and Applications (14 papers), Medical Imaging and Pathology Studies (11 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Minggang Su is often cited by papers focused on Medical Imaging Techniques and Applications (14 papers), Medical Imaging and Pathology Studies (11 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Minggang Su collaborates with scholars based in China, United States and Bangladesh. Minggang Su's co-authors include Rong Tian, Anren Kuang, Fanglan Li, Lin Li, Guohua Shen, Ye Tian, Jiancheng Zeng, Liqun Zou, Chong Jiang and Ming Jiang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Medicine.

In The Last Decade

Minggang Su

70 papers receiving 435 citations

Peers

Minggang Su
Minggang Su
Citations per year, relative to Minggang Su Minggang Su (= 1×) peers Shamim Ahmed Shamim

Countries citing papers authored by Minggang Su

Since Specialization
Citations

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

Fields of papers citing papers by Minggang Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minggang Su

This figure shows the co-authorship network connecting the top 25 collaborators of Minggang Su. A scholar is included among the top collaborators of Minggang Su 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 Minggang Su. Minggang Su 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
3.
Huang, Rui, et al.. (2025). 18F-DOPA Uptake by Stellate Ganglion on PET/CT Masquerading Medullary Thyroid Carcinoma Metastasis. Clinical Nuclear Medicine. 50(11). e654–e655.
4.
Li, Xiaohui, et al.. (2025). Increased 68Ga-DOTATATE Uptake in Brown Adipose Tissue in a Case of Head and Neck Paraganglioma. Clinical Nuclear Medicine. 50(5). 456–457. 1 indexed citations
6.
Li, Dan, et al.. (2024). Diffuse lymphoma involvement of the spinal cord showed on [18F]FDG PET/MRI. Nuclear Medicine Review. 27(0). 24–27.
7.
Su, Minggang, et al.. (2024). Diagnostic value of dual-time point 68Ga-PSMA PET/CT image for benign and malignant lesions in patients with prostate cancer. Abdominal Radiology. 49(9). 3214–3219. 1 indexed citations
10.
Xie, Hongsheng, Yuhao Li, Xiaoai Wu, et al.. (2023). The image quality, amyloid-β detectability, and acquisition time of clinical florbetapir positron emission tomography in Alzheimer’s disease and healthy adults. Quantitative Imaging in Medicine and Surgery. 13(12). 7765–7776. 1 indexed citations
11.
Tian, Rong, et al.. (2021). Intrapatient repeatability of background 18F-FDG uptake on PET/CT. Quantitative Imaging in Medicine and Surgery. 11(9). 4172–4180. 5 indexed citations
12.
Chen, Haotian, et al.. (2020). Mediastinal 99mTc-Methylene Diphosphonate Accumulation in a Patient With Primary Mediastinal Soft Tissue Giant Cell Tumor. Clinical Nuclear Medicine. 45(6). 477–479. 2 indexed citations
13.
Chen, Haotian, et al.. (2020). Solitary Hard Palate Langerhans Cell Histiocytosis Demonstrated on PET/CT Scan in an Adult. Clinical Nuclear Medicine. 45(10). 811–812. 3 indexed citations
14.
Su, Minggang, et al.. (2019). Isolated Small Bowel Metastasis From Gastric Cancer Detected by 18F-FDG PET/CT. Clinical Nuclear Medicine. 44(10). 840–841. 3 indexed citations
16.
Liang, Meng, et al.. (2017). Muscle Involvement of Multiple Myeloma Revealed by FDG PET/CT. Clinical Nuclear Medicine. 42(4). 300–302. 4 indexed citations
17.
Shen, Guohua, et al.. (2015). Primary glioblastoma of the cerebellar vermis: A case report. Oncology Letters. 10(1). 402–404. 3 indexed citations
18.
Jiang, Chong, et al.. (2015). The Deauville 5-Point Scale Improves the Prognostic Value of Interim FDG PET/CT in Extranodal Natural Killer/T-Cell Lymphoma. Clinical Nuclear Medicine. 40(10). 767–773. 22 indexed citations
19.
Su, Minggang, et al.. (2015). 18F-FDG PET/CT and MRI Findings in a Patient With Anti-GABAB Receptor Encephalitis. Clinical Nuclear Medicine. 40(6). 515–517. 18 indexed citations
20.
Su, Minggang, Rong Tian, Ye Tian, et al.. (2010). Recognition of fibrous dysplasia of bone mimicking skeletal metastasis on 18F-FDG PET/CT imaging. Skeletal Radiology. 40(3). 295–302. 1 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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