Fangfei Ge

549 total citations
21 papers, 333 citations indexed

About

Fangfei Ge is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Fangfei Ge has authored 21 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 10 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Fangfei Ge's work include Functional Brain Connectivity Studies (20 papers), Neural dynamics and brain function (10 papers) and Advanced Neuroimaging Techniques and Applications (10 papers). Fangfei Ge is often cited by papers focused on Functional Brain Connectivity Studies (20 papers), Neural dynamics and brain function (10 papers) and Advanced Neuroimaging Techniques and Applications (10 papers). Fangfei Ge collaborates with scholars based in China, United States and Australia. Fangfei Ge's co-authors include Tianming Liu, Yu Zhao, Lei Guo, Qinglin Dong, Tuo Zhang, Ning Qiang, Shu Zhang, Hanbo Chen, Xi Jiang and Xianqiao Wang and has published in prestigious journals such as Cerebral Cortex, IEEE Transactions on Biomedical Engineering and Human Brain Mapping.

In The Last Decade

Fangfei Ge

21 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fangfei Ge China	12	281	172	20	15	15	21	333
Yujie Li China	11	205 0.7×	120 0.7×	12 0.6×	9 0.6×	6 0.4×	17	334
Seyedeh-Rezvan Farahibozorg United Kingdom	9	303 1.1×	87 0.5×	11 0.6×	13 0.9×	6 0.4×	13	341
Bradley Caron United States	8	278 1.0×	117 0.7×	31 1.6×	13 0.9×	13 0.9×	12	398
Soorena Salari Iran	5	178 0.6×	52 0.3×	51 2.5×	15 1.0×	13 0.9×	7	286
Bellec Pierre	3	271 1.0×	105 0.6×	59 3.0×	27 1.8×	17 1.1×	3	339
Zhiguo Luo China	10	246 0.9×	51 0.3×	20 1.0×	6 0.4×	13 0.9×	27	339
Lewis John	2	244 0.9×	83 0.5×	56 2.8×	26 1.7×	10 0.7×	2	308
JungHoe Kim South Korea	5	270 1.0×	127 0.7×	52 2.6×	9 0.6×	44 2.9×	7	345
Renping Yu China	9	223 0.8×	84 0.5×	39 1.9×	8 0.5×	53 3.5×	29	327
Yasser Ghanbari United States	8	172 0.6×	36 0.2×	17 0.8×	10 0.7×	17 1.1×	15	289

Countries citing papers authored by Fangfei Ge

Since Specialization

Citations

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

Fields of papers citing papers by Fangfei Ge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fangfei Ge

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ge, Fangfei, et al.. (2025). Hydrogel-Based Therapeutic Strategies for Periodontal Tissue Regeneration: Advances, Challenges, and Future Perspectives. Pharmaceutics. 17(11). 1382–1382. 1 indexed citations

Li, Qing, Qinglin Dong, Fangfei Ge, et al.. (2021). Simultaneous spatial-temporal decomposition for connectome-scale brain networks by deep sparse recurrent auto-encoder. Brain Imaging and Behavior. 15(5). 2646–2660. 11 indexed citations

Liu, Shengfeng, Fangfei Ge, Lin Zhao, et al.. (2021). NAS-optimized topology-preserving transfer learning for differentiating cortical folding patterns. Medical Image Analysis. 77. 102316–102316. 6 indexed citations

Qiang, Ning, Qinglin Dong, Fangfei Ge, et al.. (2020). Deep Variational Autoencoder for Mapping Functional Brain Networks. IEEE Transactions on Cognitive and Developmental Systems. 13(4). 841–852. 24 indexed citations

Zhao, Shijie, Xintao Hu, Qinglin Dong, et al.. (2020). Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning. Brain Connectivity. 10(2). 72–82. 13 indexed citations

Zhang, Tuo, Xiao Li, Xi Jiang, et al.. (2020). Cortical 3-hinges could serve as hubs in cortico-cortical connective network. Brain Imaging and Behavior. 14(6). 2512–2529. 22 indexed citations

Qiang, Ning, Qinglin Dong, Wei Zhang, et al.. (2020). Modeling task-based fMRI data via deep belief network with neural architecture search. Computerized Medical Imaging and Graphics. 83. 101747–101747. 29 indexed citations

Dai, Haixing, et al.. (2020). Optimize CNN Model for FMRI Signal Classification Via Adanet-Based Neural Architecture Search. 1399–1403. 7 indexed citations

Dong, Qinglin, Fangfei Ge, Ning Qiang, et al.. (2019). Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network. IEEE Transactions on Biomedical Engineering. 67(6). 1739–1748. 31 indexed citations

10.

Zhao, Yu, Haixing Dai, Wei Zhang, Fangfei Ge, & Tianming Liu. (2019). Two-Stage Spatial Temporal Deep Learning Framework For Functional Brain Network Modeling. 1576–1580. 14 indexed citations

11.

Ge, Fangfei, Shu Zhang, Heng Huang, et al.. (2019). Exploring Intrinsic Functional Differences of Gyri, Sulci and 2-Hinge, 3-Hinge Joints on Cerebral Cortex. 1585–1589. 5 indexed citations

12.

Zhao, Yu, Fangfei Ge, & Tianming Liu. (2018). Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization. Medical Image Analysis. 47. 111–126. 21 indexed citations

13.

Ge, Fangfei, Hanbo Chen, Tuo Zhang, et al.. (2018). A novel framework for analyzing cortical folding patterns based on sulcal baselines and gyral crestlines. 1043–1047. 3 indexed citations

14.

Zhang, Tuo, Hanbo Chen, Mir Jalil Razavi, et al.. (2018). Exploring 3‐hinge gyral folding patterns among HCP Q3 868 human subjects. Human Brain Mapping. 39(10). 4134–4149. 20 indexed citations

15.

Liu, Huan, Shu Zhang, Xi Jiang, et al.. (2018). The Cerebral Cortex is Bisectionally Segregated into Two Fundamentally Different Functional Units of Gyri and Sulci. Cerebral Cortex. 29(10). 4238–4252. 28 indexed citations

16.

Chen, Hanbo, Yujie Li, Fangfei Ge, et al.. (2017). Gyral net: A new representation of cortical folding organization. Medical Image Analysis. 42. 14–25. 25 indexed citations

17.

Ge, Fangfei, Xiao Li, Mir Jalil Razavi, et al.. (2017). Denser Growing Fiber Connections Induce 3-hinge Gyral Folding. Cerebral Cortex. 28(3). 1064–1075. 36 indexed citations

18.

Zhao, Yu, Hanbo Chen, Yujie Li, et al.. (2016). Connectome-scale group-wise consistent resting-state network analysis in autism spectrum disorder. NeuroImage Clinical. 12. 23–33. 24 indexed citations

19.

Lv, Jinglei, Armin Iraji, Hanbo Chen, et al.. (2016). Group-wise sparse representation of brain states reveal network abnormalities in mild traumatic brain injury. 11. 58–61. 2 indexed citations

20.

Ge, Fangfei, Jinglei Lv, Xintao Hu, et al.. (2015). Deriving ADHD biomarkers with sparse coding based network analysis. 22–25. 6 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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