Hanxue Gu

826 total citations · 1 hit paper
12 papers, 378 citations indexed

About

Hanxue Gu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Hanxue Gu has authored 12 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Hanxue Gu's work include AI in cancer detection (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Medical Image Segmentation Techniques (2 papers). Hanxue Gu is often cited by papers focused on AI in cancer detection (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Medical Image Segmentation Techniques (2 papers). Hanxue Gu collaborates with scholars based in United States. Hanxue Gu's co-authors include Haoyu Dong, Maciej A. Mazurowski, Jichen Yang, Nicholas Konz, Yixin Zhang, Bin Deng, Stefan A. Carp, Katharina Hoebel, Jayashree Kalpathy–Cramer and Ken Chang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Medical Imaging and Medical Image Analysis.

In The Last Decade

Hanxue Gu

8 papers receiving 368 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Segment anything model for medical image analysis: An experimental study

2023 342 citations Maciej A. Mazurowski, Haoyu Dong et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hanxue Gu United States	5	143	140	100	64	39	12	378
Haoyu Dong United States	4	128 0.9×	139 1.0×	100 1.0×	51 0.8×	38 1.0×	10	361
Nicholas Konz United States	5	135 0.9×	180 1.3×	120 1.2×	53 0.8×	41 1.1×	11	474
Jichen Yang United States	6	155 1.1×	145 1.0×	107 1.1×	70 1.1×	37 0.9×	19	481
Adnan Haider South Korea	16	203 1.4×	170 1.2×	93 0.9×	44 0.7×	34 0.9×	34	448
Kejuan Yue China	7	241 1.7×	203 1.4×	87 0.9×	38 0.6×	38 1.0×	17	400
Liang Zeng China	6	203 1.4×	132 0.9×	116 1.2×	110 1.7×	24 0.6×	21	442
Jeremiah Neubert United States	7	134 0.9×	136 1.0×	88 0.9×	43 0.7×	45 1.2×	36	410
Tianbao Zhou China	5	112 0.8×	210 1.5×	130 1.3×	44 0.7×	41 1.1×	9	449
Xiaozheng Xie China	5	128 0.9×	93 0.7×	131 1.3×	34 0.5×	34 0.9×	12	344

Countries citing papers authored by Hanxue Gu

Since Specialization

Citations

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

Fields of papers citing papers by Hanxue Gu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanxue Gu

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

All Works

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12 of 12 papers shown

1.

Gu, Hanxue, et al.. (2025). How to Efficiently Annotate Images for Best-Performing Deep Learning-Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model. Journal of Imaging Informatics in Medicine. 38(5). 3235–3247. 2 indexed citations

2.

Gu, Hanxue, Haoyu Dong, Jichen Yang, & Maciej A. Mazurowski. (2025). How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model. 3(May 2025). 88–120. 5 indexed citations

3.

Gu, Hanxue, Robert K. Lark, Roger H. French, et al.. (2025). Deep learning automates Cobb angle measurement compared with multi-expert observers. 2(1).

4.

Chen, Yaqian, et al.. (2025). Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2. IEEE Transactions on Medical Imaging. PP. 1–1.

5.

Konz, Nicholas, Hanxue Gu, Haoyu Dong, et al.. (2025). ContourDiff: Unpaired Medical Image Translation with Structural Consistency. 3(November 2025). 711–727. 1 indexed citations

6.

Gu, Hanxue, et al.. (2025). Breast density in MRI: an AI-based quantification and relationship to assessment in mammography. npj Breast Cancer. 11(1). 115–115.

7.

Harouni, Majid, Haoyu Dong, Hanxue Gu, et al.. (2024). A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI. Scientific Reports. 14(1). 5383–5383. 4 indexed citations

8.

Dong, Haoyu, Nicholas Konz, Hanxue Gu, & Maciej A. Mazurowski. (2024). Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time Adaptation. 5046–5055.

9.

Dong, Haoyu, et al.. (2023). SWSSL: Sliding Window-Based Self-Supervised Learning for Anomaly Detection in High-Resolution Images. IEEE Transactions on Medical Imaging. 42(12). 3860–3870. 7 indexed citations

10.

Mazurowski, Maciej A., Haoyu Dong, Hanxue Gu, et al.. (2023). Segment anything model for medical image analysis: An experimental study. Medical Image Analysis. 89. 102918–102918. 342 indexed citations breakdown →

11.

Deng, Bin, Hanxue Gu, Ken Chang, et al.. (2023). FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction. IEEE Transactions on Medical Imaging. 42(8). 2439–2450. 13 indexed citations

12.

Deng, Bin, Hanxue Gu, & Stefan A. Carp. (2021). Deep learning enabled high-speed image reconstruction for breast diffuse optical tomography. 7–7. 4 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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