Shu‐Yen Wan

791 total citations
29 papers, 539 citations indexed

About

Shu‐Yen Wan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Shu‐Yen Wan has authored 29 papers receiving a total of 539 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 5 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Shu‐Yen Wan's work include Medical Image Segmentation Techniques (13 papers), Digital Image Processing Techniques (5 papers) and Image Retrieval and Classification Techniques (5 papers). Shu‐Yen Wan is often cited by papers focused on Medical Image Segmentation Techniques (13 papers), Digital Image Processing Techniques (5 papers) and Image Retrieval and Classification Techniques (5 papers). Shu‐Yen Wan collaborates with scholars based in Taiwan, United States and India. Shu‐Yen Wan's co-authors include William E. Higgins, F. Holly Coleman, R. Alberto Travagli, Shih-Wei Lin, Kuo‐Ching Ying, Lun‐Jou Lo, Erik L. Ritman, Hsiu‐Hsia Lin, Jiann-Der Lee and Chiung‐Shing Huang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Shu‐Yen Wan

27 papers receiving 513 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shu‐Yen Wan 227 67 64 60 52 29 539
Yavuz Erdem 229 1.0× 30 0.4× 87 1.4× 16 0.3× 38 0.7× 73 727
Andrea U. J. Mewes 417 1.8× 278 4.1× 26 0.4× 14 0.2× 118 2.3× 8 878
Roman Goldenberg 361 1.6× 161 2.4× 42 0.7× 12 0.2× 118 2.3× 32 618
Pengcheng Xi 195 0.9× 145 2.2× 29 0.5× 7 0.1× 70 1.3× 66 737
Su Huang 284 1.3× 227 3.4× 51 0.8× 9 0.1× 122 2.3× 46 515
S. J. Pöppl 58 0.3× 51 0.8× 98 1.5× 11 0.2× 182 3.5× 34 672
Klaus Tönnies 235 1.0× 120 1.8× 48 0.8× 3 0.1× 109 2.1× 61 487
Michael E. Leventon 1.1k 4.7× 176 2.6× 47 0.7× 9 0.1× 168 3.2× 16 1.3k
Xufeng Yao 192 0.8× 92 1.4× 9 0.1× 10 0.2× 25 0.5× 47 430
Wenpeng Gao 197 0.9× 90 1.3× 50 0.8× 5 0.1× 165 3.2× 49 586

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
1.
Gerber, Kate, Moshé Lazar, Stephen Burke, et al.. (2024). Novel Use of SCOUT® Reflector for Target Localization in Preoperative Breast Radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 120(2). e307–e307.
2.
Wan, Shu‐Yen, et al.. (2021). Disturbance-Region Removal on Landmark-less Registration of Craniofacial Images Acquired by CBCT and 3D Photography. International Journal of Emerging Technology and Advanced Engineering. 11(3). 1–7. 2 indexed citations
3.
Ying, Kuo‐Ching, Shih-Wei Lin, & Shu‐Yen Wan. (2014). Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm. International Journal of Production Research. 52(19). 5735–5747. 49 indexed citations
4.
Lin, Hsiu‐Hsia, et al.. (2013). Artifact-Resistant Superimposition of Digital Dental Models and Cone-Beam Computed Tomography Images. Journal of Oral and Maxillofacial Surgery. 71(11). 1933–1947. 54 indexed citations
5.
Wan, Shu‐Yen, Wen‐Jeng Lee, Kai‐Yuan Tzen, et al.. (2010). Registration of Micro-Computed Tomography and Histological Images of the Guinea Pig Cochlea to Construct an Ear Model Using an Iterative Closest Point Algorithm. Annals of Biomedical Engineering. 38(5). 1719–1727. 19 indexed citations
6.
Wan, Shu‐Yen, F. Holly Coleman, & R. Alberto Travagli. (2007). Glucagon-like peptide-1 excites pancreas-projecting preganglionic vagal motoneurons. American Journal of Physiology-Gastrointestinal and Liver Physiology. 292(6). G1474–G1482. 71 indexed citations
7.
Wan, Shu‐Yen, et al.. (2005). Efficient fuzzy-connectedness segmentation using symmetric convolution and adaptive thresholding. 2. 905–908. 1 indexed citations
8.
Harting, Jens, et al.. (2003). RealityGrid : high performance computing, visualisation, computational steering and teragrids. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 2(2). 4–7. 2 indexed citations
9.
Wan, Shu‐Yen & William E. Higgins. (2003). Symmetric region growing. IEEE Transactions on Image Processing. 12(9). 1007–1015. 131 indexed citations
10.
Lee, Jiann-Der, et al.. (2003). Compressing sets of similar images using hybrid compression model. 617–620. 2 indexed citations
11.
Lee, Jiann-Der, et al.. (2003). A HYBRID COMPRESSION MODEL FOR CLUSTERS OF SIMILAR MEDICAL IMAGES. Biomedical Engineering Applications Basis and Communications. 15(1). 38–45. 1 indexed citations
12.
Ritman, Erik L., et al.. (2003). Toward reliable multigenerational analysis of anatomical trees in 3D high-resolution CT images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5031. 178–178. 7 indexed citations
13.
Wan, Shu‐Yen, Erik L. Ritman, & William E. Higgins. (2002). Multi-generational analysis and visualization of the vascular tree in 3D micro-CT images. Computers in Biology and Medicine. 32(2). 55–71. 38 indexed citations
14.
Wan, Shu‐Yen, et al.. (2002). Seed-invariant region growing: its properties and applications to 3-D medical CT images. 1. 710–713. 1 indexed citations
15.
Wan, Shu‐Yen, et al.. (2002). Three-dimensional topology preserving reduction on the 4-subfields. IEEE Transactions on Pattern Analysis and Machine Intelligence. 24(12). 1594–1605. 34 indexed citations
16.
Lee, Jiann-Der, et al.. (2001). DESIGN AND IMPLEMENTATION OF A PC-BASED MULTIMEDIA BIOSIGNAL INTEGRATION SYSTEM. Biomedical Engineering Applications Basis and Communications. 13(6). 267–275. 1 indexed citations
17.
Wan, Shu‐Yen, Erik L. Ritman, & William E. Higgins. (2001). <title>Multigenerational analysis and visualization of large 3D vascular images</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4322. 766–775. 1 indexed citations
18.
Sherbondy, Anthony J., Atilla P. Kiraly, J.P. Helferty, et al.. (2000). Virtual bronchoscopic approach for combining 3D CT and endoscopic video. Proceedings of SPIE - The International Society for Optical Engineering. 3978. 104–116. 1 indexed citations
19.
Bulbulia, Richard, et al.. (2000). The endothelin(A) (ETA) receptor antagonist, BSF 302146, is a potent inhibitor of porcine vein graft thickening, in vivo. British Journal of Pharmacology. 131. 5 indexed citations
20.
Wan, Shu‐Yen & William E. Higgins. (2000). Symmetric region growing. 96–99 vol.2. 9 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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