Youngjin Yoo

1.5k citations
30 papers · 748 indexed · 1 hit paper · h-index 13
Topics
Advanced MRI Techniques and Applications (6 papers)Image and Signal Denoising Methods (4 papers)Medical Imaging Techniques and Applications (4 papers)

In The Last Decade

Youngjin Yoo

29 papers receiving 727 citations

Hit Papers

Deep 3D Convolutional Encoder Networks With Shortcuts for...20162026201920222016100200300

Peers

Youngjin Yoo
Comparison fields: 5 of 84
  • Radiology, Nuclear Medicine and Imaging 388
  • Computer Vision and Pattern Recognition 228
  • Artificial Intelligence 203
  • Neurology 155
  • Pathology and Forensic Medicine 102
Replace Alfiia Galimzianova with:
Alfiia Galimzianova United States
Tom Brosch Germany
Hidetaka Arimura Japan
Kelei He China
Phillip Chlap Australia
Amod Jog United States
Nico Karssemeijer Netherlands
Shunxing Bao United States
April Khademi Canada
Dimitris Samaras United States
Youngjin Yoo relative to Alfiia Galimzianova United States Alfiia Galimzianova's profile →
Citations per field
00.5×3.5×
Alfiia Galimzianova · 1×
Citations per year

Countries citing papers authored by Youngjin Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Youngjin Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Youngjin Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Youngjin Yoo. A scholar is included among the top collaborators of Youngjin Yoo 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 Youngjin Yoo. Youngjin Yoo 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 4
3 0
4 14
5 28
6 17
7 12
8 3
9 94
10 62
11 50
12 1
13 22
14 12
15 16
16 1
17 1
18 6
19 3
20
Performances of Heuristic Algorithms for Consolidated Transportation with Weight and Volume Constraints
1

About Youngjin Yoo

Youngjin Yoo is a scholar working on Neurology, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 30 papers that have together received 748 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (6 papers), Image and Signal Denoising Methods (4 papers) and Medical Imaging Techniques and Applications (4 papers). The work is most often cited by research in Health Informatics (46 citations), Neurology (155 citations) and Radiology, Nuclear Medicine and Imaging (388 citations). Youngjin Yoo has collaborated with scholars based in Canada, United States and South Korea. Frequent co-authors include Roger Tam, David K.B. Li, Anthony Traboulsee, Lisa Tang, Tom Brosch, Shannon Kolind, Irene M. Vavasour, Alex L. MacKay, Alexander Rauscher and Dorin Comaniciu. Their work appears in journals such as Neurology, International Journal of Radiation Oncology*Biology*Physics and Magnetic Resonance in Medicine.

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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