Dong Hye Ye

7.7k citations
53 papers · 787 indexed · h-index 17
Topics
Medical Imaging Techniques and Applications (13 papers)Medical Image Segmentation Techniques (9 papers)Advanced X-ray and CT Imaging (8 papers)

In The Last Decade

Dong Hye Ye

49 papers receiving 757 citations

Peers

Dong Hye Ye
Comparison fields: 5 of 97
  • Computer Vision and Pattern Recognition 337
  • Radiology, Nuclear Medicine and Imaging 248
  • Biomedical Engineering 146
  • Aerospace Engineering 141
  • Artificial Intelligence 112
Replace Yuping Duan with:
Yuping Duan China
Yicheng Wu China
Tran Minh Quan South Korea
Mehdi S. M. Sajjadi United States
David Tucker United States
Travis McPhail United States
Sejung Yang South Korea
Fahad Shamshad Pakistan
Wenxian Zheng China
Pei Dong China
Dong Hye Ye relative to Yuping Duan China Yuping Duan's profile →
Citations per field
00.5×6.4×
Yuping Duan · 1×
Citations per year

Countries citing papers authored by Dong Hye Ye

Since Specialization
Citations

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

Fields of papers citing papers by Dong Hye Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong Hye Ye. 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 Dong Hye Ye. The network helps show where Dong Hye Ye may publish in the future.

Co-authorship network of co-authors of Dong Hye Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Dong Hye Ye. A scholar is included among the top collaborators of Dong Hye Ye 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 Dong Hye Ye. Dong Hye Ye 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 1
2 0
3 1
4 4
5 2
6 6
7 13
8 22
9 11
10 18
11 2
12 3
13 96
14 16
15 3
16 10
17 16
18 7
19 1
20 82

About Dong Hye Ye

Dong Hye Ye is a scholar working on Radiology, Nuclear Medicine and Imaging, Biophysics and Computer Vision and Pattern Recognition, having authored 53 papers that have together received 787 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (13 papers), Medical Image Segmentation Techniques (9 papers) and Advanced X-ray and CT Imaging (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (337 citations), Structural Biology (19 citations) and Radiology, Nuclear Medicine and Imaging (248 citations). Dong Hye Ye has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Charles A. Bouman, Christos Davatzikos, Juan Wachs, Jihun Hamm, Mathias Kölsch, Kilian M. Pohl, Ragini Verma, Timothy H. Chung, K. Sauer and Jean‐Baptiste Thibault. Their work appears in journals such as Analytical Chemistry, IEEE Transactions on Medical Imaging and Sensors.

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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