Stephen M. Smith

210.9k citations
401 papers · 142.5k · 59 hit papers · h-index 122

Impact in

    • Functional Brain Connectivity Studies
    • Neural dynamics and brain function
    • EEG and Brain-Computer Interfaces
    • Neural and Behavioral Psychology Studies
    • Advanced Neuroimaging Techniques and Applications
    • Advanced MRI Techniques and Applications

Papers in

Stephen M. Smith

388 papers receiving 140.5k citations

Stephen M. Smith's Hit Papers

SARS-CoV-2 is associated with changes in brain structure in UK Biobank 2022 · 952 citations
9520+4+8Years since publication10002.0k3.0k

Peers

Stephen M. Smith
Comparison fields: 5 of 233
  • Cognitive Neuroscience 74.5k
  • Radiology, Nuclear Medicine and Imaging 50.4k
  • Computational Mathematics 657
  • Psychiatry and Mental health 13.2k
  • Neurology 7.3k
Replace Alan C. Evans with:
Alan C. Evans Canada
Mark Jenkinson United Kingdom
Timothy E.J. Behrens United Kingdom
Paul M. Thompson United States
Bruce Fischl United States
Arthur W. Toga United States
Christian F. Beckmann United Kingdom
Abraham Z. Snyder United States
Karl Friston United Kingdom
Marcus E. Raichle United States
Stephen M. Smith relative to Alan C. Evans Canada Alan C. Evans's profile →
Citations per field
00.5×3.2×
Alan C. Evans · 1×
Citations per year

Countries citing papers authored by Stephen M. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 401 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Advances in functional and structural MR image analysis and implementation as FSL
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200411074
2
Fast robust automated brain extraction
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20028717
3
FSL
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20118378
4
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images
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20028297
5
A global optimisation method for robust affine registration of brain images
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20015694
6
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
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20015472
7
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
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20065441
8
Correspondence of the brain's functional architecture during activation and rest
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20094220
9
Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference
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20084201
10
The WU-Minn Human Connectome Project: An overview
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20133771
11
Consistent resting-state networks across healthy subjects
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20063549
12
A multi-modal parcellation of human cerebral cortex
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20163192
13
Investigations into resting-state connectivity using independent component analysis
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20052771
14
Permutation inference for the general linear model
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20142612
15
Characterization and propagation of uncertainty in diffusion‐weighted MR imaging
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20032559
16
SUSAN—A New Approach to Low Level Image Processing
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19972550
17
Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data
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20012304
18
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging
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20042179
19
Bayesian analysis of neuroimaging data in FSL
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20081980
20
Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
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20031955

About Stephen M. Smith

Stephen M. Smith is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pediatrics, Perinatology and Child Health and Artificial Intelligence, having authored 401 papers that have together received 142.5k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (176 papers), Advanced Neuroimaging Techniques and Applications (108 papers), Advanced MRI Techniques and Applications (90 papers), Neural dynamics and brain function (61 papers), EEG and Brain-Computer Interfaces (29 papers), Medical Image Segmentation Techniques (28 papers), Blind Source Separation Techniques (19 papers) and Fetal and Pediatric Neurological Disorders (18 papers). The work is most often cited by research in Cognitive Neuroscience (74.5k citations), Radiology, Nuclear Medicine and Imaging (50.4k citations), Computational Mathematics (657 citations), Psychiatry and Mental health (13.2k citations) and Neurology (7.3k citations). Stephen M. Smith has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Mark Jenkinson, Christian F. Beckmann, Timothy E.J. Behrens, Mark W. Woolrich, Thomas E. Nichols, Michael Brady, Paul M. Matthews, Peter Bannister, J. Michael Brady and Heidi Johansen‐Berg. Their work appears in journals such as NeuroImage, Human Brain Mapping, Proceedings of the National Academy of Sciences, Brain and Nature Neuroscience.

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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