Anil Rao

1.6k total citations · 1 hit paper
19 papers, 1.1k citations indexed

About

Anil Rao is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Anil Rao has authored 19 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Cognitive Neuroscience and 5 papers in Artificial Intelligence. Recurrent topics in Anil Rao's work include Medical Image Segmentation Techniques (5 papers), Functional Brain Connectivity Studies (5 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). Anil Rao is often cited by papers focused on Medical Image Segmentation Techniques (5 papers), Functional Brain Connectivity Studies (5 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). Anil Rao collaborates with scholars based in United Kingdom, Italy and Germany. Anil Rao's co-authors include Paul M. Matthews, Stephen M. Smith, Brandon Whitcher, Achim Gass, Ricarda Menke, Gwenaëlle Douaud, Andreas U. Monsch, Saâd Jbabdi, Timothy E.J. Behrens and Gordon Kindlmann and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and NeuroImage.

In The Last Decade

Anil Rao

19 papers receiving 1.1k citations

Hit Papers

DTI measures in crossing-fibre areas: Increased diffusion... 2010 2026 2015 2020 2010 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anil Rao United Kingdom 13 588 402 249 226 94 19 1.1k
R. Allom United Kingdom 9 434 0.7× 428 1.1× 298 1.2× 175 0.8× 100 1.1× 15 1.3k
Andrea D. Klunder United States 14 675 1.1× 582 1.4× 476 1.9× 244 1.1× 127 1.4× 23 1.4k
Chadwick P. Ward United States 11 482 0.8× 356 0.9× 455 1.8× 371 1.6× 84 0.9× 19 1.1k
Robert Donnino United States 16 454 0.8× 224 0.6× 143 0.6× 212 0.9× 116 1.2× 50 1.2k
Diana Rosas United States 7 558 0.9× 739 1.8× 410 1.6× 181 0.8× 50 0.5× 7 1.5k
Norihide Maikusa Japan 23 460 0.8× 470 1.2× 474 1.9× 158 0.7× 44 0.5× 77 1.2k
Frank Ezekiel United States 18 706 1.2× 383 1.0× 348 1.4× 324 1.4× 63 0.7× 24 1.4k
Jonathan B. Chalk Australia 18 467 0.8× 484 1.2× 200 0.8× 141 0.6× 28 0.3× 37 1.2k
Julie L. Winterburn Canada 8 257 0.4× 392 1.0× 237 1.0× 143 0.6× 87 0.9× 10 810
Rhian Jenkins United Kingdom 4 337 0.6× 404 1.0× 419 1.7× 334 1.5× 37 0.4× 4 1.0k

Countries citing papers authored by Anil Rao

Since Specialization
Citations

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

Fields of papers citing papers by Anil Rao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anil Rao

This figure shows the co-authorship network connecting the top 25 collaborators of Anil Rao. A scholar is included among the top collaborators of Anil Rao 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 Anil Rao. Anil Rao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Rao, Anil, João M. Monteiro, & Janaı́na Mourão-Miranda. (2017). Predictive modelling using neuroimaging data in the presence of confounds. NeuroImage. 150. 23–49. 60 indexed citations
2.
Monteiro, João M., Anil Rao, John Shawe‐Taylor, & Janaı́na Mourão-Miranda. (2016). A multiple hold-out framework for Sparse Partial Least Squares. Journal of Neuroscience Methods. 271. 182–194. 33 indexed citations
3.
Portugal, Liana Catarina Lima, Tiago Arruda Sanchez, Anil Rao, et al.. (2016). Decoding negative affect personality trait from patterns of brain activation to threat stimuli. NeuroImage. 145(Pt B). 337–345. 22 indexed citations
4.
Rao, Anil, João M. Monteiro, & Janaı́na Mourão-Miranda. (2016). Prediction of clinical scores from neuroimaging data with censored likelihood gaussian processes. 1–4. 1 indexed citations
5.
Rao, Anil, João M. Monteiro, John Ashburner, et al.. (2015). A Comparison of Strategies for Incorporating Nuisance Variables into Predictive Neuroimaging Models. 61–64. 2 indexed citations
6.
Monteiro, João M., Anil Rao, John Ashburner, John Shawe‐Taylor, & Janaı́na Mourão-Miranda. (2015). Multivariate Effect Ranking via Adaptive Sparse PLS. 25–28. 3 indexed citations
7.
Weiss, Nick, Daniel Rueckert, & Anil Rao. (2013). Multiple Sclerosis Lesion Segmentation Using Dictionary Learning and Sparse Coding. Lecture notes in computer science. 16(Pt 1). 735–742. 57 indexed citations
8.
Newbould, Rexford D., Sam R. Miller, Neil Upadhyay, et al.. (2013). T1-Weighted Sodium MRI of the Articulator Cartilage in Osteoarthritis: A Cross Sectional and Longitudinal Study. PLoS ONE. 8(8). e73067–e73067. 26 indexed citations
9.
Douaud, Gwenaëlle, Ricarda Menke, Achim Gass, et al.. (2013). Brain Microstructure Reveals Early Abnormalities more than Two Years prior to Clinical Progression from Mild Cognitive Impairment to Alzheimer's Disease. Journal of Neuroscience. 33(5). 2147–2155. 143 indexed citations
10.
Bhatia, Kanwal K., Anil Rao, Anthony N. Price, et al.. (2013). Hierarchical Manifold Learning for Regional Image Analysis. IEEE Transactions on Medical Imaging. 33(2). 444–461. 18 indexed citations
11.
Bhatia, Kanwal K., Anil Rao, Anthony N. Price, et al.. (2012). Hierarchical Manifold Learning. Lecture notes in computer science. 15(Pt 1). 512–519. 12 indexed citations
12.
13.
Inkster, Becky, Anil Rao, Khanum Ridler, et al.. (2010). Structural Brain Changes in Patients with Recurrent Major Depressive Disorder Presenting with Anxiety Symptoms. Journal of Neuroimaging. 21(4). 375–382. 49 indexed citations
14.
Douaud, Gwenaëlle, Saâd Jbabdi, Timothy E.J. Behrens, et al.. (2010). DTI measures in crossing-fibre areas: Increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease. NeuroImage. 55(3). 880–890. 404 indexed citations breakdown →
15.
Inkster, Becky, Anil Rao, Khanum Ridler, et al.. (2010). Genetic variation in GOLM1 and prefrontal cortical volume in Alzheimer's disease. Neurobiology of Aging. 33(3). 457–465. 10 indexed citations
16.
Filippini, Nicola, Anil Rao, Sally Wetten, et al.. (2008). Anatomically-distinct genetic associations of APOE ɛ4 allele load with regional cortical atrophy in Alzheimer's disease. NeuroImage. 44(3). 724–728. 123 indexed citations
17.
Smith, Stephen M., Anil Rao, Nicola De Stefano, et al.. (2007). Longitudinal and cross-sectional analysis of atrophy in Alzheimer's disease: Cross-validation of BSI, SIENA and SIENAX. NeuroImage. 36(4). 1200–1206. 91 indexed citations
18.
Rao, Anil, T.F. Cootes, & Daniel Rueckert. (2006). Hierarchical Statistical Shape Analysis and Prediction of Sub-Cortical Brain Structures. 56. 75–75. 1 indexed citations
19.
Chandrashekara, R., Anil Rao, Gerardo I. Sanchez-Ortiz, Raad Mohiaddin, & Daniel Rueckert. (2003). Construction of a Statistical Model for Cardiac Motion Analysis Using Nonrigid Image Registration. Lecture notes in computer science. 18. 599–610. 48 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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