Hengfei Cui

642 total citations
27 papers, 365 citations indexed

About

Hengfei Cui is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Hengfei Cui has authored 27 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Hengfei Cui's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Medical Image Segmentation Techniques (6 papers) and Advanced Neural Network Applications (6 papers). Hengfei Cui is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Medical Image Segmentation Techniques (6 papers) and Advanced Neural Network Applications (6 papers). Hengfei Cui collaborates with scholars based in China, Singapore and Hong Kong. Hengfei Cui's co-authors include Yong Xia, Yanning Zhang, Lei Jiang, Junjie Zhang, Yan Li, Hanlin Yin, Xiuwei Zhang, Yifan Wang, Jiayi Chen and Liang Zhong and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Medical Imaging.

In The Last Decade

Hengfei Cui

26 papers receiving 357 citations

Peers

Hengfei Cui

RNMI

CVPR

PRM

Jingyang Zhang China

Byoung-Dai Lee South Korea

Mostafa Ghelich Oghli Iran

Mingquan Lin United States

Laquan Li China

Rupert Brooks Canada

Ryoungwoo Jang South Korea

Ruibin Feng United States

Adeel Abbasi Pakistan

Tabea Kossen Germany

Jingyang Zhang China

Hengfei Cui

160 ×0.8

RNMI

162 ×1.1

CVPR

112 ×0.8

73 ×0.9

27 ×0.4

PRM

Citations per year, relative to Hengfei Cui Hengfei Cui (= 1×) peers Jingyang Zhang

Countries citing papers authored by Hengfei Cui

Since Specialization

Citations

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

Fields of papers citing papers by Hengfei Cui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hengfei Cui

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

All Works

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20 of 20 papers shown

Jia, Haozhe, Yan Li, Hengfei Cui, et al.. (2024). DisControlFace: Adding Disentangled Control to Diffusion Autoencoder for One-shot Explicit Facial Image Editing. 6793–6802. 2 indexed citations

Cui, Hengfei, Yan Li, Yifan Wang, et al.. (2024). Toward Accurate Cardiac MRI Segmentation With Variational Autoencoder-Based Unsupervised Domain Adaptation. IEEE Transactions on Medical Imaging. 43(8). 2924–2936. 10 indexed citations

Chen, Jiayi, Benteng Ma, Hengfei Cui, & Yong Xia. (2024). Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 11439–11449. 13 indexed citations

Wang, Hongyu, et al.. (2024). Robust Stochastic Neural Ensemble Learning With Noisy Labels for Thoracic Disease Classification. IEEE Transactions on Medical Imaging. 43(6). 2180–2190. 2 indexed citations

Cui, Hengfei, Yifan Wang, Yan Li, et al.. (2023). An Improved Combination of Faster R-CNN and U-Net Network for Accurate Multi-Modality Whole Heart Segmentation. IEEE Journal of Biomedical and Health Informatics. 27(7). 3408–3419. 21 indexed citations

Cui, Hengfei, et al.. (2023). Deformable medical image registration with global–local transformation network and region similarity constraint. Computerized Medical Imaging and Graphics. 108. 102263–102263. 9 indexed citations

Li, Yan, et al.. (2023). Unsupervised Domain Adaptation via Variational Autoencoder with Explicit and Implicit Feature Alignment for Cardiac Segmentation. 34. 532–537. 1 indexed citations

Xia, Yong, et al.. (2023). AATSN: Anatomy Aware Tumor Segmentation Network for PET-CT volumes and images using a lightweight fusion-attention mechanism. Computers in Biology and Medicine. 157. 106748–106748. 16 indexed citations

Cui, Hengfei, et al.. (2022). Deep U-Net architecture with curriculum learning for myocardial pathology segmentation in multi-sequence cardiac magnetic resonance images. Knowledge-Based Systems. 249. 108942–108942. 14 indexed citations

10.

Cui, Hengfei, Yan Li, Lei Jiang, et al.. (2022). Improving myocardial pathology segmentation with U-Net++ and EfficientSeg from multi-sequence cardiac magnetic resonance images. Computers in Biology and Medicine. 151. 106218–106218. 8 indexed citations

11.

Jiang, Lei, et al.. (2022). Multiple GANs guided by self-attention mechanism for automatic cardiac image segmentation. 15–15.

12.

Cui, Hengfei, et al.. (2021). Bidirectional cross-modality unsupervised domain adaptation using generative adversarial networks for cardiac image segmentation. Computers in Biology and Medicine. 136. 104726–104726. 24 indexed citations

13.

Cui, Hengfei, et al.. (2021). Multiscale attention guided U-Net architecture for cardiac segmentation in short-axis MRI images. Computer Methods and Programs in Biomedicine. 206. 106142–106142. 52 indexed citations

14.

Zhang, Xiuwei, et al.. (2021). A robust discriminative multi-atlas label fusion method for hippocampus segmentation from MR image. Computer Methods and Programs in Biomedicine. 208. 106197–106197. 5 indexed citations

15.

Cui, Hengfei, et al.. (2021). Unsupervised Three-Dimensional Tubular Structure Segmentation via Filter Combination. International Journal of Computational Intelligence Systems. 14(1). 3 indexed citations

16.

Cui, Hengfei. (2020). Supervised Filter Learning for Coronary Artery Vesselness Enhancement Diffusion in Coronary CT Angiography Images. International Journal of Computational Intelligence Systems. 13(1). 488–488. 2 indexed citations

17.

Cui, Hengfei, Yong Xia, & Yanning Zhang. (2020). Supervised machine learning for coronary artery lumen segmentation in intravascular ultrasound images. International Journal for Numerical Methods in Biomedical Engineering. 36(7). e3348–e3348. 12 indexed citations

18.

Zhang, Junjie, Yong Xia, Hengfei Cui, & Yanning Zhang. (2018). Pulmonary nodule detection in medical images: A survey. Biomedical Signal Processing and Control. 43. 138–147. 59 indexed citations

19.

Cui, Hengfei, Min Wan, Junmei Zhang, et al.. (2016). Fast Marching and Runge–Kutta Based Method for Centreline Extraction of Right Coronary Artery in Human Patients. Cardiovascular Engineering and Technology. 7(2). 159–169. 9 indexed citations

20.

Cui, Hengfei, Desheng Wang, Min Wan, et al.. (2014). Coronary artery segmentation via Hessian filter and curve-skeleton extraction. 93–98. 7 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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