Bryan M. Williams

1.9k total citations
63 papers, 1.1k citations indexed

About

Bryan M. Williams is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Bryan M. Williams has authored 63 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Biomedical Engineering and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Bryan M. Williams's work include Optical Coherence Tomography Applications (13 papers), Glaucoma and retinal disorders (12 papers) and Retinal Imaging and Analysis (10 papers). Bryan M. Williams is often cited by papers focused on Optical Coherence Tomography Applications (13 papers), Glaucoma and retinal disorders (12 papers) and Retinal Imaging and Analysis (10 papers). Bryan M. Williams collaborates with scholars based in United Kingdom, United States and China. Bryan M. Williams's co-authors include Yalin Zheng, Baidaa Al‐Bander, Waleed Al‐Nuaimy, Gabriela Czanner, Rachel Williams, Chen Xu, S. Rao Vallabhaneni, Majid A. Al-Taee, Yaochun Shen and Harry Pratt and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The FASEB Journal.

In The Last Decade

Bryan M. Williams

61 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bryan M. Williams United Kingdom 14 577 410 354 224 112 63 1.1k
Ahmed Shalaby United States 21 673 1.2× 259 0.6× 288 0.8× 149 0.7× 256 2.3× 84 1.5k
Rahele Kafieh Iran 18 1.0k 1.8× 586 1.4× 306 0.9× 555 2.5× 133 1.2× 87 1.4k
Emanuele Torti Italy 17 280 0.5× 148 0.4× 160 0.5× 153 0.7× 109 1.0× 67 838
Debdoot Sheet India 16 751 1.3× 343 0.8× 650 1.8× 371 1.7× 329 2.9× 80 1.4k
Qiaoliang Li China 14 599 1.0× 329 0.8× 448 1.3× 132 0.6× 99 0.9× 49 985
Behdad Dashtbozorg Netherlands 17 1.1k 1.8× 735 1.8× 479 1.4× 147 0.7× 79 0.7× 69 1.3k
Francesco Leporati Italy 16 221 0.4× 105 0.3× 185 0.5× 198 0.9× 123 1.1× 91 914
Malaya Kumar Nath India 21 534 0.9× 309 0.8× 493 1.4× 107 0.5× 375 3.3× 67 1.3k
Elli Angelopoulou Germany 18 373 0.6× 247 0.6× 1.1k 3.1× 73 0.3× 183 1.6× 59 1.5k

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-authorship network of co-authors of Bryan M. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan M. Williams. A scholar is included among the top collaborators of Bryan M. Williams 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 Bryan M. Williams. Bryan M. Williams 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.
Rahmani, Hossein, et al.. (2025). Recent Advances of Continual Learning in Computer Vision: An Overview. IET Computer Vision. 19(1). 4 indexed citations
2.
Jiang, Zheheng, Hossein Rahmani, Sue Black, & Bryan M. Williams. (2025). 3D Points Splatting for real-time dynamic Hand Reconstruction. Pattern Recognition. 162. 111426–111426.
3.
Williams, Bryan M., et al.. (2025). Demonstrable and anatomy-driven knuckle identification via crease map segmentation. Signal Image and Video Processing. 19(4). 2 indexed citations
4.
Williams, Bryan M., et al.. (2022). Ensemble-Based Bounding Box Regression for Enhanced Knuckle Localization. Sensors. 22(4). 1569–1569. 3 indexed citations
5.
Jiang, Richard, Ce Zhang, Bryan M. Williams, et al.. (2022). Robust Brain Age Estimation Based on sMRI via Nonlinear Age-Adaptive Ensemble Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30. 2146–2156. 11 indexed citations
6.
Williams, Bryan M., Robert K. May, Michael Evans, et al.. (2022). Optimizing Terahertz Waveform Selection of a Pharmaceutical Film Coating Process Using Recurrent Network. IEEE Transactions on Terahertz Science and Technology. 12(4). 392–400. 9 indexed citations
7.
Williams, Bryan M., Silvester Czanner, Srinivasan Kavitha, et al.. (2021). EffUnet-SpaGen: An Efficient and Spatial Generative Approach to Glaucoma Detection. Journal of Imaging. 7(6). 92–92. 13 indexed citations
8.
Angelov, Plamen, et al.. (2021). Automated Person Identification Framework Based on Fingernails and Dorsal Knuckle Patterns. 2021 IEEE Symposium Series on Computational Intelligence (SSCI). 1–8. 7 indexed citations
9.
Ahmad, Sajjad, Vito Romano, Christof Seifarth, et al.. (2020). En-face analysis of the human limbal lymphatic vasculature. Experimental Eye Research. 201. 108278–108278. 5 indexed citations
10.
11.
Williams, Bryan M., Davide Borroni, Rongjun Liu, et al.. (2019). An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study. Diabetologia. 63(2). 419–430. 111 indexed citations
12.
Pratt, Harry, et al.. (2019). Learning the features of diabetic retinopathy with convolutional neural networks. Lancaster EPrints (Lancaster University). 1 indexed citations
13.
Al‐Bander, Baidaa, Bryan M. Williams, Waleed Al‐Nuaimy, et al.. (2018). Dense Fully Convolutional Segmentation of the Optic Disc and Cup in Colour Fundus for Glaucoma Diagnosis. Symmetry. 10(4). 87–87. 139 indexed citations
14.
O’Brien, Fiona, Bryan M. Williams, Harry Pratt, & Richard Barrett‐Jolley. (2018). CVS role of TRPV: from single channels to HRV assessment with Artificial Intelligence.. The FASEB Journal. 32(S1). 1 indexed citations
15.
Pratt, Harry, Bryan M. Williams, Baidaa Al‐Bander, et al.. (2017). Automatic Detection and Distinction of Retinal Vessel Bifurcations and Crossings in Colour Fundus Photography. Journal of Imaging. 4(1). 4–4. 12 indexed citations
16.
Madden, Peter W., Vito Romano, Yue Dong, et al.. (2017). Deformation velocity imaging using optical coherence tomography and its applications to the cornea. Biomedical Optics Express. 8(12). 5579–5579. 23 indexed citations
17.
Al‐Bander, Baidaa, Waleed Al‐Nuaimy, Majid A. Al-Taee, Bryan M. Williams, & Yalin Zheng. (2016). Diabetic Macular Edema Grading Based on Deep Neural Networks. 121–128. 27 indexed citations
18.
Lin, Hungyen, Yue Dong, Daniel Markl, et al.. (2016). Measurement of the Intertablet Coating Uniformity of a Pharmaceutical Pan Coating Process With Combined Terahertz and Optical Coherence Tomography In-Line Sensing. Journal of Pharmaceutical Sciences. 106(4). 1075–1084. 74 indexed citations
19.
Williams, Bryan M., et al.. (2007). Pairs of largest circuits in 3-connected matroids. Linear Algebra and its Applications. 427(2-3). 313–316. 1 indexed citations
20.
Williams, Bryan M.. (1963). CONGENITAL CERVICAL AND VAGINAL ATRESIA*. BJOG An International Journal of Obstetrics & Gynaecology. 70(2). 301–302. 4 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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