Marc Modat

20.0k total citations · 2 hit papers
178 papers, 7.1k citations indexed

About

Marc Modat is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Physiology. According to data from OpenAlex, Marc Modat has authored 178 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Radiology, Nuclear Medicine and Imaging, 49 papers in Computer Vision and Pattern Recognition and 26 papers in Physiology. Recurrent topics in Marc Modat's work include Medical Image Segmentation Techniques (45 papers), Advanced Neuroimaging Techniques and Applications (38 papers) and Medical Imaging Techniques and Applications (33 papers). Marc Modat is often cited by papers focused on Medical Image Segmentation Techniques (45 papers), Advanced Neuroimaging Techniques and Applications (38 papers) and Medical Imaging Techniques and Applications (33 papers). Marc Modat collaborates with scholars based in United Kingdom, United States and France. Marc Modat's co-authors include Sébastien Ourselin, Nick C. Fox, M. Jorge Cardoso, Gerard R. Ridgway, Josephine Barnes, David M. Cash, Manja Lehmann, David J. Hawkes, Zeike A. Taylor and Jonathan D. Rohrer and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Marc Modat

173 papers receiving 7.0k 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.

Fast free-form deformation using graphics processing units

2009 738 citations Marc Modat, Gerard R. Ridgway et al. Computer Methods and Programs in Biomedicine profile →
NiftyNet: a deep-learning platform for medical imaging

2018 363 citations Eli Gibson, Wenqi Li et al. Computer Methods and Programs in Biomedicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marc Modat United Kingdom	44	3.4k	1.5k	1.3k	1.2k	1.0k	178	7.1k
Koen Van Leemput United States	36	2.3k 0.7×	2.3k 1.6×	873 0.7×	1.5k 1.2×	555 0.5×	104	6.6k
Paul Aljabar United Kingdom	45	3.5k 1.0×	2.0k 1.4×	807 0.6×	1.8k 1.5×	388 0.4×	100	8.0k
Jürgen Fripp Australia	37	1.7k 0.5×	750 0.5×	1.1k 0.9×	926 0.8×	982 1.0×	251	5.2k
Nicholas J. Tustison United States	33	5.4k 1.6×	1.8k 1.2×	1.1k 0.9×	3.5k 2.9×	841 0.8×	133	12.1k
Lothar R. Schad Germany	56	8.4k 2.5×	615 0.4×	812 0.6×	1.7k 1.4×	588 0.6×	406	12.8k
William R. Crum United Kingdom	36	2.2k 0.6×	1.1k 0.8×	1.5k 1.2×	1.5k 1.3×	1.2k 1.2×	97	5.9k
Torsten Rohlfing United States	48	3.4k 1.0×	1.7k 1.2×	524 0.4×	1.9k 1.6×	303 0.3×	124	8.2k
Colin Studholme United States	48	3.4k 1.0×	2.2k 1.5×	863 0.7×	1.6k 1.3×	365 0.4×	147	8.4k
John G. Sled Canada	52	5.1k 1.5×	1.7k 1.1×	1.3k 1.0×	2.6k 2.2×	938 0.9×	239	13.9k
Rolf A. Heckemann United Kingdom	35	1.8k 0.5×	1.5k 1.0×	1.0k 0.8×	936 0.8×	489 0.5×	92	5.6k

Countries citing papers authored by Marc Modat

Since Specialization

Citations

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

Fields of papers citing papers by Marc Modat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marc Modat

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

All Works

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20 of 20 papers shown

Canas, Liane S., Joseph Donovan, Nguyễn Thụy Thương Thương, et al.. (2025). Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis. PLoS ONE. 20(5). e0321655–e0321655. 1 indexed citations

Murray, Benjamin, Richard Brown, Eric Kerfoot, et al.. (2024). Lazy Resampling: Fast and information preserving preprocessing for deep learning. Computer Methods and Programs in Biomedicine. 257. 108422–108422. 1 indexed citations

Nderitu, Paul, Samantha Mann, M. Jorge Cardoso, et al.. (2024). Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning. SHILAP Revista de lepidopterología. 4(1). 167–167. 2 indexed citations

Kinnersley, Ben, et al.. (2024). Radiogenomic biomarkers for immunotherapy in glioblastoma: A systematic review of magnetic resonance imaging studies. Neuro-Oncology Advances. 6(1). vdae055–vdae055. 3 indexed citations

Antonelli, Michela, Rose Penfold, Liane S. Canas, et al.. (2023). SARS-CoV-2 infection following booster vaccination: Illness and symptom profile in a prospective, observational community-based case-control study. Journal of Infection. 87(6). 506–515. 20 indexed citations

Wood, David, et al.. (2023). Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection. Clinical Neuroradiology. 33(4). 943–956. 17 indexed citations

Kläser, Kerstin, Marc Modat, David Atkinson, et al.. (2021). A Multi-Channel Uncertainty-Aware Multi-Resolution Network for MR to CT Synthesis. Applied Sciences. 11(4). 1667–1667. 10 indexed citations

Markiewicz, Paweł, Julian C. Matthews, John Ashburner, et al.. (2021). Uncertainty analysis of MR-PET image registration for precision neuro-PET imaging. NeuroImage. 232. 117821–117821. 10 indexed citations

Modat, Marc, Jamie R. McClelland, Alexis Dimitriadis, et al.. (2021). The impact of unscheduled gaps and iso-centre sequencing on the biologically effective dose in Gamma Knife radiosurgery.. PubMed Central. 7(3). 213–221. 6 indexed citations

10.

Convery, Rhian S., Mollie Neason, David M. Cash, et al.. (2020). Basal forebrain atrophy in frontotemporal dementia. NeuroImage Clinical. 26. 102210–102210. 12 indexed citations

11.

Ma, Da, M. Jorge Cardoso, María A. Zuluaga, et al.. (2020). Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellar cortex of the Tc1 mouse model of down syndrome – a comprehensive morphometric analysis with active staining contrast-enhanced MRI. NeuroImage. 223. 117271–117271. 4 indexed citations

12.

Canas, Liane S., Carole H. Sudre, Enrico De Vita, et al.. (2019). Prion disease diagnosis using subject-specific imaging biomarkers within a multi-kernel Gaussian process. NeuroImage Clinical. 24. 102051–102051. 4 indexed citations

13.

Gibson, Eli, Wenqi Li, Carole H. Sudre, et al.. (2018). NiftyNet: a deep-learning platform for medical imaging. Computer Methods and Programs in Biomedicine. 158. 113–122. 363 indexed citations breakdown →

14.

McClelland, Jamie R., Marc Modat, Simon Arridge, et al.. (2017). A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images. Physics in Medicine and Biology. 62(11). 4273–4292. 39 indexed citations

15.

Andrews, Katharine, Chris Frost, Marc Modat, et al.. (2015). Acceleration of hippocampal atrophy rates in asymptomatic amyloidosis. Neurobiology of Aging. 39. 99–107. 18 indexed citations

16.

Prados, Ferrán, et al.. (2014). Robust and fully-automated atrophy measures for multiple sclerosis disease.. UCL Discovery (University College London). 1 indexed citations

17.

Cardoso, M. Jorge, Kelvin K. Leung, Marc Modat, et al.. (2013). STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation. Medical Image Analysis. 17(6). 671–684. 170 indexed citations

18.

Keihaninejad, Shiva, Natalie S. Ryan, Ian B. Malone, et al.. (2012). The Importance of Group-Wise Registration in Tract Based Spatial Statistics Study of Neurodegeneration: A Simulation Study in Alzheimer's Disease. PLoS ONE. 7(11). e45996–e45996. 71 indexed citations

19.

Melbourne, Andrew, et al.. (2011). Adaptive Neonate Brain Segmentation. UCL Discovery (University College London). 10 indexed citations

20.

Winston, Gavin P., Pankaj Daga, Jason Stretton, et al.. (2011). Optic radiation tractography and vision in anterior temporal lobe resection. Annals of Neurology. 71(3). 334–341. 69 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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