Bryan M. Williams

61 papers receiving 1.1k citations

Peers

Bryan M. Williams
Comparison fields: 5 of 127
  • Ophthalmology 352
  • Radiology, Nuclear Medicine and Imaging 542
  • Computer Vision and Pattern Recognition 348
  • Biophysics 50
  • Health Informatics 9
Replace Rahele Kafieh with:
Rahele Kafieh Iran
Malaya Kumar Nath India
Behdad Dashtbozorg Netherlands
Manuel G. Penedo Spain
Qiaoliang Li China
Debdoot Sheet India
Désiré Sidibé France
Yixiong Liang China
Emanuele Torti Italy
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Citations per year

Countries citing papers authored by Bryan M. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Bryan M. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan M. Williams. 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 Bryan M. Williams. The network helps show where Bryan M. Williams may publish in the future.

Co-authors

The 25 scholars most cited alongside Bryan M. Williams, 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 Bryan M. Williams Line = papers co-authored together Bryan M. Williams links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019205
2 2018140
3 2019116
4 201784
5 201675
6 202269
7 201954
8 201845
9 201631
10 201627
11 201725
12 201723
13 201715
14 202114
15 202014
16 202212
17 201712
18 200212
19 202312
20 202011

About Bryan M. Williams

Bryan M. Williams is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Ophthalmology and Electrical and Electronic Engineering, having authored 63 papers that have together received 1.2k indexed citations. Recurring topics across this work include Optical Coherence Tomography Applications (12 papers), Retinal Imaging and Analysis (10 papers), Photoacoustic and Ultrasonic Imaging (10 papers), Glaucoma and retinal disorders (9 papers), Digital Imaging for Blood Diseases (5 papers), Terahertz technology and applications (5 papers), Corneal surgery and disorders (5 papers) and Image Processing Techniques and Applications (4 papers). The work is most often cited by research in Ophthalmology (352 citations), Radiology, Nuclear Medicine and Imaging (542 citations), Computer Vision and Pattern Recognition (348 citations), Biophysics (50 citations) and Health Informatics (9 citations). Bryan M. Williams has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Yalin Zheng, Baidaa Al‐Bander, Waleed Al‐Nuaimy, Gabriela Czanner, Chen Xu, S. Rao Vallabhaneni, Rachel Williams, Yaochun Shen, Majid A. Al-Taee and Harry Pratt. Their work appears in journals such as Optics Express, PLoS ONE, Pattern Recognition, BJOG An International Journal of Obstetrics & Gynaecology and Experimental Eye Research.

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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