Shu‐Yen Wan

27 papers receiving 513 citations

Peers

Shu‐Yen Wan
Comparison fields: 5 of 103
  • Computer Vision and Pattern Recognition 227
  • Radiology, Nuclear Medicine and Imaging 67
  • Surgery 64
  • Industrial and Manufacturing Engineering 60
  • Biomedical Engineering 52
Replace Pengcheng Xi with:
Pengcheng Xi Canada
Yavuz Erdem Türkiye
Andrea U. J. Mewes United States
Xufeng Yao China
N.G. Durdle Canada
Roman Goldenberg Israel
S. J. Pöppl Germany
Yingmei Wei China
Klaus Tönnies Germany
Shu‐Yen Wan relative to Pengcheng Xi Canada Pengcheng Xi's profile →
Citations per field
00.5×8.6×
Pengcheng Xi · 1×
Citations per year

Countries citing papers authored by Shu‐Yen Wan

Since Specialization
Citations

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

Fields of papers citing papers by Shu‐Yen Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu‐Yen Wan. 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 Shu‐Yen Wan. The network helps show where Shu‐Yen Wan may publish in the future.

Co-authorship network of co-authors of Shu‐Yen Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Shu‐Yen Wan. A scholar is included among the top collaborators of Shu‐Yen Wan 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 Shu‐Yen Wan. Shu‐Yen Wan 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
#WorkIndexed citations
1 0
2 2
3 49
4 54
5 19
6 71
7 1
8
RealityGrid : high performance computing, visualisation, computational steering and teragrids
2
9 131
10 2
11 7
12 1
13 1
14 38
15 34
16 1
17 1
18
Virtual bronchoscopic approach for combining 3D CT and endoscopic video
1
19
The endothelin(A) (ETA) receptor antagonist, BSF 302146, is a potent inhibitor of porcine vein graft thickening, in vivo
5
20 16

About Shu‐Yen Wan

Shu‐Yen Wan is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Biophysics, having authored 29 papers that have together received 539 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (13 papers), Digital Image Processing Techniques (5 papers) and Image Retrieval and Classification Techniques (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (44 citations), Computer Vision and Pattern Recognition (227 citations) and Orthodontics (35 citations). Shu‐Yen Wan has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include William E. Higgins, F. Holly Coleman, R. Alberto Travagli, Kuo‐Ching Ying, Shih-Wei Lin, Lun‐Jou Lo, Erik L. Ritman, Hsiu‐Hsia Lin, Jiann-Der Lee and Chiung‐Shing Huang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and International Journal of Radiation Oncology*Biology*Physics.

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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