David Raffelt

6.4k total citations · 3 hit papers
24 papers, 3.6k citations indexed

About

David Raffelt is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Psychiatry and Mental health. According to data from OpenAlex, David Raffelt has authored 24 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Cognitive Neuroscience and 5 papers in Psychiatry and Mental health. Recurrent topics in David Raffelt's work include Advanced Neuroimaging Techniques and Applications (20 papers), Advanced MRI Techniques and Applications (7 papers) and Functional Brain Connectivity Studies (5 papers). David Raffelt is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (20 papers), Advanced MRI Techniques and Applications (7 papers) and Functional Brain Connectivity Studies (5 papers). David Raffelt collaborates with scholars based in Australia, United Kingdom and Belgium. David Raffelt's co-authors include Alan Connelly, Jacques‐Donald Tournier, Robert E. Smith, Thijs Dhollander, Ben Jeurissen, Chun‐Hung Yeh, Daan Christiaens, Maximilian Pietsch, Gerard R. Ridgway and Olivier Salvado and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Brain.

In The Last Decade

David Raffelt

24 papers receiving 3.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

2019 1.7k citations Jacques‐Donald Tournier, Robert E. Smith et al. NeuroImage profile →
Apparent Fibre Density: A novel measure for the analysis of diffusion-weighted magnetic resonance images

2011 434 citations David Raffelt, Jacques‐Donald Tournier et al. NeuroImage profile →
Investigating white matter fibre density and morphology using fixel-based analysis

2016 414 citations David Raffelt, Jacques‐Donald Tournier et al. NeuroImage profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Raffelt Australia	17	2.8k	1.3k	771	505	470	24	3.6k
Thijs Dhollander Australia	22	2.9k 1.0×	1.8k 1.3×	767 1.0×	393 0.8×	406 0.9×	62	4.1k
Daan Christiaens United Kingdom	17	2.6k 0.9×	1.3k 1.0×	792 1.0×	307 0.6×	345 0.7×	41	3.6k
Rita G. Nunes Portugal	23	3.2k 1.1×	1.6k 1.2×	862 1.1×	340 0.7×	709 1.5×	84	4.5k
Kazi Akhter United States	9	2.1k 0.8×	1.1k 0.9×	516 0.7×	495 1.0×	359 0.8×	9	2.8k
Robert E. Smith Australia	12	2.7k 1.0×	1.9k 1.4×	607 0.8×	343 0.7×	364 0.8×	18	3.8k
Anastasia Yendiki United States	33	2.2k 0.8×	1.8k 1.4×	498 0.6×	567 1.1×	375 0.8×	96	3.9k
Helen D’Arceuil United States	27	2.8k 1.0×	1.7k 1.2×	663 0.9×	322 0.6×	348 0.7×	49	4.1k
Wim Van Hecke Belgium	38	2.0k 0.7×	798 0.6×	464 0.6×	646 1.3×	590 1.3×	102	4.1k
Chun‐Hung Yeh Taiwan	15	2.3k 0.8×	1.3k 1.0×	583 0.8×	261 0.5×	280 0.6×	38	3.0k
Peter J. Basser United States	7	3.7k 1.3×	983 0.7×	934 1.2×	493 1.0×	403 0.9×	9	4.3k

Countries citing papers authored by David Raffelt

Since Specialization

Citations

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

Fields of papers citing papers by David Raffelt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Raffelt

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Smith, Robert E., et al.. (2022). Quantitative streamlines tractography: methods and inter-subject normalisation. SHILAP Revista de lepidopterología. 1–25. 25 indexed citations

Mito, Remika, Thijs Dhollander, Ying Xia, et al.. (2020). In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data. NeuroImage Clinical. 28. 102479–102479. 19 indexed citations

Tournier, Jacques‐Donald, Robert E. Smith, David Raffelt, et al.. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage. 202. 116137–116137. 1682 indexed citations breakdown →

Mito, Remika, Thijs Dhollander, David Raffelt, et al.. (2018). IC‐P‐184: ADVANCED DIFFUSION MRI ENABLES IN VIVO INVESTIGATION OF MICROSTRUCTURAL HETEROGENEITY OF WHITE MATTER HYPERINTENSITIES IN ALZHEIMER'S DISEASE. Alzheimer s & Dementia. 14(7S_Part_2). 1 indexed citations

Raffelt, David, Thijs Dhollander, Elaine Lui, et al.. (2017). Fibre-specific white matter changes in multiple sclerosis patients with optic neuritis. NeuroImage Clinical. 17. 60–68. 43 indexed citations

Mito, Remika, David Raffelt, Thijs Dhollander, et al.. (2017). Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment. Brain. 141(3). 888–902. 207 indexed citations

Küpper, Hanna, Manfred Kudernatsch, Tom Pieper, et al.. (2016). Predicting hand function after hemidisconnection. Brain. 139(9). 2456–2468. 27 indexed citations

Raffelt, David, Jacques‐Donald Tournier, Robert E. Smith, et al.. (2016). Investigating white matter fibre density and morphology using fixel-based analysis. NeuroImage. 144(Pt A). 58–73. 414 indexed citations breakdown →

Raffelt, David, Robert E. Smith, Gerard R. Ridgway, et al.. (2015). Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres. NeuroImage. 117. 40–55. 270 indexed citations

10.

Calamante, Fernando, Robert E. Smith, Jacques‐Donald Tournier, David Raffelt, & Alan Connelly. (2015). Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping. NeuroImage. 117. 284–293. 39 indexed citations

11.

Pannek, Kerstin, et al.. (2015). Structural connectivity of the anterior cingulate in children with unilateral cerebral palsy due to white matter lesions. NeuroImage Clinical. 9. 498–505. 25 indexed citations

12.

Calamante, Fernando, Richard A. J. Masterton, Jacques‐Donald Tournier, et al.. (2013). Track-weighted functional connectivity (TW-FC): A tool for characterizing the structural–functional connections in the brain. NeuroImage. 70. 199–210. 34 indexed citations

13.

Willats, Lisa, David Raffelt, Robert E. Smith, et al.. (2013). Quantification of track-weighted imaging (TWI): Characterisation of within-subject reproducibility and between-subject variability. NeuroImage. 87. 18–31. 26 indexed citations

14.

Pannek, Kerstin, David Raffelt, Christopher J. Bell, Jane L. Mathias, & Stephen Rose. (2012). HOMOR: Higher Order Model Outlier Rejection for high b-value MR diffusion data. NeuroImage. 63(2). 835–842. 34 indexed citations

15.

Raffelt, David, Jacques‐Donald Tournier, ‪Stuart Crozier‬, et al.. (2012). IC‐P‐108: Apparent fibre density: A novel MRI approach that identifies specific white matter tracts affected in Alzheimer's disease and MCI. Alzheimer s & Dementia. 8(4S_Part_2). 2 indexed citations

16.

Raffelt, David, Jacques‐Donald Tournier, ‪Stuart Crozier‬, et al.. (2012). Voxel-based analysis of Alzheimer's Disease using apparent fibre density. Queensland's institutional digital repository (The University of Queensland). 2 indexed citations

17.

Raffelt, David, Jacques‐Donald Tournier, Stephen Rose, et al.. (2011). Apparent Fibre Density: A novel measure for the analysis of diffusion-weighted magnetic resonance images. NeuroImage. 59(4). 3976–3994. 434 indexed citations breakdown →

18.

Raffelt, David, Jacques‐Donald Tournier, Jürgen Fripp, et al.. (2011). Symmetric diffeomorphic registration of fibre orientation distributions. NeuroImage. 56(3). 1171–1180. 197 indexed citations

19.

Raffelt, David, Jacques‐Donald Tournier, ‪Stuart Crozier‬, Alan Connelly, & Olivier Salvado. (2011). Reorientation of fiber orientation distributions using apodized point spread functions. Magnetic Resonance in Medicine. 67(3). 844–855. 88 indexed citations

20.

Raffelt, David, ‪Stuart Crozier‬, Alan Connelly, Olivier Salvado, & Jacques‐Donald Tournier. (2010). Apparent Fibre Density: A New Measure for High Angular Resolution Diffusion-Weighted Image Analysis. Queensland's institutional digital repository (The University of Queensland). 575–575. 5 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.

Explore authors with similar magnitude of impact