Mark Jenkinson

109.1k citations
275 papers · 87.7k · 33 hit papers · h-index 85

Impact in

Papers in

Mark Jenkinson

268 papers receiving 86.8k citations

Mark Jenkinson's Hit Papers

The Developing Human Connectome Project Neonatal Data Release 2022 · 102 citations
1020+4+9Years since publication1k2k3k

Peers

Mark Jenkinson
Comparison fields: 5 of 197
  • Cognitive Neuroscience 31.4k
  • Radiology, Nuclear Medicine and Imaging 24.5k
  • Psychiatry and Mental health 12k
  • Neurology 5.2k
  • Computer Vision and Pattern Recognition 7.2k
Replace John Ashburner with:
John Ashburner United Kingdom
Bruce R. Fischl United States
Alan Charles Evans Canada
Timothy E.J. Behrens United Kingdom
Paul McMahan Matthews United Kingdom
Stephen M. Smith United Kingdom
Anders Martin Dale United States
Christian F. Beckmann United Kingdom
Mark W. Woolrich United Kingdom
Arthur W. Toga United States
Mark Jenkinson relative to John Ashburner United Kingdom John Ashburner's profile →
Citations per field
00.5×2×2.6×
John Ashburner · 1×
Citations per year

Countries citing papers authored by Mark Jenkinson

Since Specialization
Citations

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

Fields of papers citing papers by Mark Jenkinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 275 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
Hit paper breakdown →
200411443
2
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images
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20029883
3
FSL
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20118947
4
A global optimisation method for robust affine registration of brain images
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20015847
5
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
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20065627
6
The minimal preprocessing pipelines for the Human Connectome Project
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20133813
7
A multi-modal parcellation of human cerebral cortex
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20163468
8
Characterization and propagation of uncertainty in diffusion‐weighted MR imaging
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20032633
9
Bayesian analysis of neuroimaging data in FSL
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20082060
10
A Bayesian model of shape and appearance for subcortical brain segmentation
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20111948
11
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
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20091847
12
Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis
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20021819
13
Multilevel linear modelling for FMRI group analysis using Bayesian inference
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20041410
14
Multimodal population brain imaging in the UK Biobank prospective epidemiological study
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20161403
15
General multilevel linear modeling for group analysis in FMRI
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20031255
16
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank
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20171076
17
Functional connectomics from resting-state fMRI
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2013771
18
The Human Connectome Project's neuroimaging approach
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2016766
19
Advances in diffusion MRI acquisition and processing in the Human Connectome Project
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2013730
20
Common genetic variants influence human subcortical brain structures
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2015678

About Mark Jenkinson

Mark Jenkinson is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Psychiatry and Mental health and Neurology, having authored 275 papers that have together received 87.7k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (84 papers), Advanced MRI Techniques and Applications (55 papers), Advanced Neuroimaging Techniques and Applications (47 papers), Functional Brain Connectivity Studies (44 papers), Dementia and Cognitive Impairment Research (24 papers), Multiple Sclerosis Research Studies (19 papers), Acute Ischemic Stroke Management (7 papers) and Cerebrovascular and genetic disorders (7 papers). The work is most often cited by research in Cognitive Neuroscience (31.4k citations), Radiology, Nuclear Medicine and Imaging (24.5k citations), Psychiatry and Mental health (12k citations), Neurology (5.2k citations) and Computer Vision and Pattern Recognition (7.2k citations). Mark Jenkinson has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Stephen M. Smith, Timothy E.J. Behrens, Christian F. Beckmann, Mark W. Woolrich, Michael Brady, Paul McMahan Matthews, Heidi Johansen‐Berg, Nicola De Stefano, Jesper Andersson and Yongyue Zhang. Their work appears in journals such as NeuroImage, Human Brain Mapping, Magnetic Resonance in Medicine, Medical Image Analysis and Brain.

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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