Jan‐Ray Liao

539 citations
33 papers · 414 · h-index 11

Impact in

Papers in

Jan‐Ray Liao

32 papers receiving 403 citations

Peers

Jan‐Ray Liao
Comparison fields: 5 of 91
  • Radiology, Nuclear Medicine and Imaging 163
  • Computer Vision and Pattern Recognition 85
  • Media Technology 23
  • Signal Processing 19
  • Atomic and Molecular Physics, and Optics 54
Replace Dmitry V. Dylov with:
Dmitry V. Dylov Russia
Pedro Serranho Portugal
B.A. Baertlein United States
Otkrist Gupta United States
Pei Dong China
Michael Iliadis United States
Li Tao United States
Ronald L. Allen United States
Michał Marcinkiewicz France
Jack Tsao Hong Kong
Jan‐Ray Liao relative to Dmitry V. Dylov Russia Dmitry V. Dylov's profile →
Citations per field
00.5×1.5×2.0×
Dmitry V. Dylov · 1×
Citations per year

Countries citing papers authored by Jan‐Ray Liao

Since Specialization
Citations

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

Fields of papers citing papers by Jan‐Ray Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan‐Ray Liao. 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 Jan‐Ray Liao. The network helps show where Jan‐Ray Liao may publish in the future.

Co-authors

The 25 scholars most cited alongside Jan‐Ray Liao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan‐Ray Liao Line = papers co-authored together Jan‐Ray Liao links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199792
2 201356
3 201442
4 201735
5 199833
6 201330
7 201020
8 199519
9 202012
10 199711
11 200010
12 20158
13 20026
14 20196
15 20104
16 20154
17 20233
18 20203
19 20022
20 20222

About Jan‐Ray Liao

Jan‐Ray Liao is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Media Technology, having authored 33 papers that have together received 414 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (10 papers), Image and Signal Denoising Methods (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), Medical Imaging Techniques and Applications (5 papers), Advanced Image Fusion Techniques (5 papers), Advanced Electrical Measurement Techniques (5 papers), Image Processing Techniques and Applications (4 papers) and MRI in cancer diagnosis (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (163 citations), Computer Vision and Pattern Recognition (85 citations), Media Technology (23 citations), Signal Processing (19 citations) and Atomic and Molecular Physics, and Optics (54 citations). Jan‐Ray Liao has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Norbert J. Pelc, John M. Pauly, Thomas J. Brosnan, Chun‐Ming Chen, Hsin‐Lun Lee, Chuen‐Horng Lin, Chun‐Chieh Chen, Jun‐Cheng Weng, Yu-Chieh Lin and Cheng‐Jian Lin. Their work appears in journals such as Magnetic Resonance in Medicine, Digital Signal Processing, Expert Systems with Applications, Signal Processing and Multidimensional Systems and Signal Processing.

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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