Shuo Han

1.4k total citations
31 papers, 267 citations indexed

About

Shuo Han is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Neurology. According to data from OpenAlex, Shuo Han has authored 31 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Computer Vision and Pattern Recognition and 8 papers in Neurology. Recurrent topics in Shuo Han's work include Advanced Neuroimaging Techniques and Applications (10 papers), Medical Image Segmentation Techniques (7 papers) and Advanced MRI Techniques and Applications (7 papers). Shuo Han is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (10 papers), Medical Image Segmentation Techniques (7 papers) and Advanced MRI Techniques and Applications (7 papers). Shuo Han collaborates with scholars based in United States, China and Australia. Shuo Han's co-authors include Jerry L. Prince, Aaron Carass, Yufan He, Yang An, Susan M. Resnick, Lotta M. Ellingsen, Ari M. Blitz, Lianrui Zuo, Yuan Xue and Xiang Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, NeuroImage and Magnetic Resonance in Medicine.

In The Last Decade

Shuo Han

27 papers receiving 266 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuo Han United States 8 127 71 60 58 58 31 267
Rémi Giraud France 7 82 0.6× 71 1.0× 33 0.6× 43 0.7× 104 1.8× 12 283
Leonie Henschel Germany 6 209 1.6× 67 0.9× 46 0.8× 26 0.4× 82 1.4× 9 393
Jessica Lebenberg France 11 153 1.2× 40 0.6× 64 1.1× 21 0.4× 48 0.8× 32 350
Elaine Williams United Kingdom 6 137 1.1× 24 0.3× 53 0.9× 77 1.3× 61 1.1× 6 332
Ashley Rumple United States 9 111 0.9× 31 0.4× 95 1.6× 31 0.5× 57 1.0× 14 319
Santiago Estrada Germany 5 214 1.7× 56 0.8× 41 0.7× 21 0.4× 82 1.4× 12 398
Sophie Adler United Kingdom 14 214 1.7× 39 0.5× 131 2.2× 72 1.2× 42 0.7× 25 484
Kilian Hett United States 8 70 0.6× 55 0.8× 33 0.6× 100 1.7× 43 0.7× 19 238
Loredana Storelli Italy 13 160 1.3× 95 1.3× 15 0.3× 47 0.8× 76 1.3× 37 501
Leon Y. Cai United States 13 264 2.1× 35 0.5× 36 0.6× 32 0.6× 49 0.8× 41 453

Countries citing papers authored by Shuo Han

Since Specialization
Citations

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

Fields of papers citing papers by Shuo Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuo Han

This figure shows the co-authorship network connecting the top 25 collaborators of Shuo Han. A scholar is included among the top collaborators of Shuo Han 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 Shuo Han. Shuo Han 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.
Edwards, Erin M., Shuo Han, Peter A. Calabresi, et al.. (2025). Cerebellar Volume Measures Differentiate Multiple Sclerosis Fallers from Non-Fallers. Brain Sciences. 15(1). 77–77.
2.
Hu, Fang, Shuo Han, Fengjie Liu, et al.. (2024). Isobicyclogermacrenal ameliorates hippocampal ferroptosis involvement in neurochemical disruptions and neuroinflammation induced by sleep deprivation in rats. Phytomedicine. 136. 156306–156306. 3 indexed citations
3.
Han, Shuo, et al.. (2023). ESPRESO: An algorithm to estimate the slice profile of a single magnetic resonance image. Magnetic Resonance Imaging. 98. 155–163. 4 indexed citations
4.
Zhang, Daiyan, et al.. (2023). Profiling targets and potential target pairs of CAR-T cell therapy in clinical trials. International Immunopharmacology. 126. 111273–111273. 1 indexed citations
5.
Han, Shuo, Lianrui Zuo, Aaron Carass, et al.. (2023). Self-Supervised Super-Resolution for Anisotropic MR Images with and Without Slice Gap. Lecture notes in computer science. 14288. 118–128. 6 indexed citations
6.
Han, Shuo, et al.. (2023). FedECS: Client Selection for Optimizing Computing Energy in Federated Learning. 1–6. 4 indexed citations
7.
Han, Shuo, et al.. (2022). Synchrotron microtomography image restoration via regularization representation and deep CNN prior. Computer Methods and Programs in Biomedicine. 226. 107181–107181. 4 indexed citations
8.
Liu, Yihao, Lianrui Zuo, Shuo Han, et al.. (2022). Coordinate Translator for Learning Deformable Medical Image Registration. Lecture notes in computer science. 13594. 98–109. 17 indexed citations
9.
10.
Xue, Yuan, Blake E. Dewey, Lianrui Zuo, et al.. (2022). Bi-directional Synthesis of Pre- and Post-contrast MRI via Guided Feature Disentanglement. Lecture notes in computer science. 13570. 55–65. 3 indexed citations
11.
Carass, Aaron, Lianrui Zuo, Yufan He, et al.. (2022). Disentangled Representation Learning for OCTA Vessel Segmentation With Limited Training Data. IEEE Transactions on Medical Imaging. 41(12). 3686–3698. 15 indexed citations
12.
Kerestes, Rebecca, Shuo Han, Srinivas Balachander, et al.. (2022). A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging. Journal of Visualized Experiments. 7 indexed citations
13.
Han, Shuo, Blake E. Dewey, Jacob C. Reinhold, et al.. (2022). Multiple Sclerosis brain lesion segmentation with different architecture ensembles. 39. 80–80. 2 indexed citations
14.
Han, Shuo, et al.. (2021). Joint Image and Label Self-super-Resolution. Lecture notes in computer science. 12965. 14–23. 3 indexed citations
15.
Han, Shuo, Yang An, Aaron Carass, Jerry L. Prince, & Susan M. Resnick. (2020). Longitudinal analysis of regional cerebellum volumes during normal aging. NeuroImage. 220. 117062–117062. 37 indexed citations
16.
Han, Shuo, Aaron Carass, Yufan He, & Jerry L. Prince. (2020). Automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization. NeuroImage. 218. 116819–116819. 47 indexed citations
17.
Han, Shuo, Aaron Carass, Xiang Li, et al.. (2019). Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly. NeuroImage Clinical. 23. 101871–101871. 34 indexed citations
18.
Han, Shuo, Yufan He, Aaron Carass, Sarah H. Ying, & Jerry L. Prince. (2019). Cerebellum parcellation with convolutional neural networks. PubMed. 10949. 19–19. 11 indexed citations
19.
Han, Shuo, Aaron Carass, & Jerry L. Prince. (2019). Hierarchical Parcellation of the Cerebellum. Lecture notes in computer science. 11766. 484–491. 2 indexed citations
20.
Han, Shuo, Aaron Carass, Xiang Li, et al.. (2018). Shortcomings of Ventricle Segmentation Using Deep Convolutional Networks. Lecture notes in computer science. 11038. 79–86. 14 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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