Xiangyang Xu

1.6k total citations
69 papers, 1.1k citations indexed

About

Xiangyang Xu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Media Technology. According to data from OpenAlex, Xiangyang Xu has authored 69 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Vision and Pattern Recognition, 26 papers in Radiology, Nuclear Medicine and Imaging and 16 papers in Media Technology. Recurrent topics in Xiangyang Xu's work include Medical Image Segmentation Techniques (18 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Image and Signal Denoising Methods (13 papers). Xiangyang Xu is often cited by papers focused on Medical Image Segmentation Techniques (18 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Image and Signal Denoising Methods (13 papers). Xiangyang Xu collaborates with scholars based in China, United States and Canada. Xiangyang Xu's co-authors include Enmin Song, Hong Liu, Guangzhi Ma, Chih‐Cheng Hung, Renchao Jin, Haichao Cao, Lianghai Jin, Hongmei Zhou, Zhentao Zuo and Xinyao Cheng and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Medical Imaging.

In The Last Decade

Xiangyang Xu

66 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiangyang Xu China 20 553 392 379 215 130 69 1.1k
Bikesh Kumar Singh India 22 567 1.0× 304 0.8× 219 0.6× 583 2.7× 103 0.8× 100 1.4k
Svitlana Zinger Netherlands 20 293 0.5× 472 1.2× 210 0.6× 201 0.9× 82 0.6× 107 1.4k
Kelei He China 16 580 1.0× 441 1.1× 135 0.4× 369 1.7× 74 0.6× 25 1.1k
Jean‐Louis Dillenseger France 18 311 0.6× 505 1.3× 134 0.4× 134 0.6× 62 0.5× 89 979
Wenjun Tan China 18 366 0.7× 207 0.5× 172 0.5× 149 0.7× 30 0.2× 94 996
Palani Thanaraj Krishnan India 14 358 0.6× 185 0.5× 198 0.5× 251 1.2× 32 0.2× 39 939
Muthu Rama Krishnan Mookiah Singapore 23 1.4k 2.5× 597 1.5× 141 0.4× 220 1.0× 37 0.3× 50 1.9k
Marcos Martín‐Fernández Spain 20 431 0.8× 498 1.3× 54 0.1× 145 0.7× 125 1.0× 68 1.1k
S.S. Furuie Brazil 16 367 0.7× 286 0.7× 145 0.4× 109 0.5× 27 0.2× 102 1.1k
Martin Rajchl Canada 22 640 1.2× 584 1.5× 186 0.5× 285 1.3× 27 0.2× 61 1.6k

Countries citing papers authored by Xiangyang Xu

Since Specialization
Citations

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

Fields of papers citing papers by Xiangyang Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangyang Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangyang Xu. A scholar is included among the top collaborators of Xiangyang Xu 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 Xiangyang Xu. Xiangyang Xu 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.
Jin, Renchao, et al.. (2025). Computer-aided diagnosis of spinal deformities based on keypoints detection in human back depth images. Biomedical Signal Processing and Control. 106. 107764–107764.
2.
Sun, S., et al.. (2025). GD-YOLO: A lightweight model for household waste image detection. Expert Systems with Applications. 279. 127525–127525. 2 indexed citations
3.
Jiang, Cuiping, et al.. (2025). Reliability of Patellar Height Measurement in Children and Adolescents on MRI. Journal of Pediatric Orthopaedics.
4.
Su, Xiaojuan, et al.. (2024). Understanding health education needs of pregnant women in China during public health emergencies: a qualitative study amidst the COVID-19 pandemic. Frontiers in Public Health. 12. 1271327–1271327. 1 indexed citations
5.
Dong, Yue, Cong Ma, Cuiping Jiang, et al.. (2024). Coronary inflammation based on pericoronary adipose tissue attenuation in type 2 diabetic mellitus: effect of diabetes management. Cardiovascular Diabetology. 23(1). 108–108. 9 indexed citations
6.
Li, Qingping, Wenqian Tang, Maomao Xi, et al.. (2024). The association of stress perception on anxiety, depression and sleep quality in parents of children with burns: The moderating effect of social support. Burns. 50(6). 1652–1661. 4 indexed citations
7.
Xu, Chengqi, et al.. (2022). Global Limb Anatomic Staging System Score correlates with the clinical outcomes in chronic limb threatening ischemia patients. International Angiology. 41(4). 303–311. 2 indexed citations
8.
Liu, Hong, et al.. (2022). A bidirectional multilayer contrastive adaptation network with anatomical structure preservation for unpaired cross-modality medical image segmentation. Computers in Biology and Medicine. 149. 105964–105964. 9 indexed citations
9.
Xia, Xinyue, Hongmei Zhou, Panpan Chen, et al.. (2021). Assessment of peripheral neuropathy in type 2 diabetes by diffusion tensor imaging: A case-control study. European Journal of Radiology. 145. 110007–110007. 7 indexed citations
10.
Li, Yumin, Xiaoyu Han, Jing Huang, et al.. (2021). Follow-up study of pulmonary sequelae in discharged COVID-19 patients with diabetes or secondary hyperglycemia. European Journal of Radiology. 144. 109997–109997. 12 indexed citations
11.
Liu, Hong, et al.. (2020). Multi-model Ensemble Learning Architecture Based on 3D CNN for Lung Nodule Malignancy Suspiciousness Classification. Journal of Digital Imaging. 33(5). 1242–1256. 55 indexed citations
12.
Liu, Hong, Haichao Cao, Enmin Song, et al.. (2019). A cascaded dual-pathway residual network for lung nodule segmentation in CT images. Physica Medica. 63. 112–121. 70 indexed citations
13.
Cao, Haichao, Hong Liu, Chih‐Cheng Hung, et al.. (2019). Dual-branch residual network for lung nodule segmentation. Applied Soft Computing. 86. 105934–105934. 99 indexed citations
14.
Liu, Hong, Jie Wang, Xiangyang Xu, et al.. (2014). A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters. Magnetic Resonance Imaging. 32(9). 1139–1155. 7 indexed citations
15.
Zhou, Yuan, Xinyao Cheng, Xiangyang Xu, & Enmin Song. (2013). Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation. Medical Image Analysis. 17(8). 892–906. 12 indexed citations
16.
17.
Liu, Hong, et al.. (2011). Fissures Segmentation Using Surface Features. Academic Radiology. 18(12). 1475–1484. 4 indexed citations
18.
Xu, Xiangyang, et al.. (2011). Ultrasound intima–media segmentation using Hough transform and dual snake model. Computerized Medical Imaging and Graphics. 36(3). 248–258. 42 indexed citations
19.
Xu, Xiangyang. (2008). Content-based Image Retrieval for Computer-aided Detection of Mammographic Masses. Journal of Chinese Computer Systems. 2 indexed citations
20.
Hu, Jian, En Luo, Enming Song, et al.. (2008). Patients’ attitudes towards online dental information and a web-based virtual reality program for clinical dentistry: A pilot investigation in China. International Journal of Medical Informatics. 78(3). 208–215. 12 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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