Olivier Colliot

12.6k total citations · 3 hit papers
156 papers, 6.5k citations indexed

About

Olivier Colliot is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Psychiatry and Mental health. According to data from OpenAlex, Olivier Colliot has authored 156 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Radiology, Nuclear Medicine and Imaging, 39 papers in Computer Vision and Pattern Recognition and 39 papers in Psychiatry and Mental health. Recurrent topics in Olivier Colliot's work include Advanced Neuroimaging Techniques and Applications (39 papers), Medical Image Segmentation Techniques (33 papers) and Dementia and Cognitive Impairment Research (31 papers). Olivier Colliot is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (39 papers), Medical Image Segmentation Techniques (33 papers) and Dementia and Cognitive Impairment Research (31 papers). Olivier Colliot collaborates with scholars based in France, Canada and United States. Olivier Colliot's co-authors include Marie Chupin, Habib Benali, Stéphane Lehéricy, Bruno Dubois, Emilie Gérardin, Rémi Cuingnet, Isabelle Bloch, Line Garnero, Marie Sarazin and Stéphane Lehéricy and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.

In The Last Decade

Olivier Colliot

152 papers receiving 6.3k 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.

Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database

2010 698 citations Marie Chupin, Olivier Colliot et al. profile →
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

2020 423 citations Junhao Wen, Elina Thibeau–Sutre et al. Medical Image Analysis profile →
Early and protective microglial activation in Alzheimer’s disease: a prospective study using¹⁸F-DPA-714 PET imaging

2016 374 citations Lorraine Hamelin, Julien Lagarde et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Olivier Colliot France	39	2.3k	1.9k	1.8k	1.6k	1.4k	156	6.5k
Ivo D. Dinov United States	46	1.4k 0.6×	741 0.4×	1.9k 1.1×	1.8k 1.1×	1.0k 0.7×	197	7.2k
Josephine Barnes United Kingdom	46	3.0k 1.3×	1.2k 0.6×	2.2k 1.2×	1.9k 1.2×	2.3k 1.6×	129	7.3k
Vladimir Fonov Canada	39	1.1k 0.5×	1.1k 0.6×	2.0k 1.1×	2.5k 1.6×	712 0.5×	146	6.8k
Yong Fan United States	38	1.5k 0.6×	1.4k 0.7×	2.8k 1.6×	2.6k 1.6×	685 0.5×	186	7.2k
William R. Crum United Kingdom	36	1.5k 0.7×	662 0.3×	1.5k 0.9×	2.2k 1.4×	1.2k 0.8×	97	5.9k
Koen Van Leemput United States	36	873 0.4×	1.1k 0.6×	1.5k 0.8×	2.3k 1.5×	555 0.4×	104	6.6k
Rolf A. Heckemann United Kingdom	35	1.0k 0.4×	1.1k 0.6×	936 0.5×	1.8k 1.2×	489 0.3×	92	5.6k
Pierrick Bourgeat Australia	37	3.4k 1.5×	1.1k 0.6×	1.6k 0.9×	1.6k 1.0×	3.7k 2.6×	229	7.2k
Owen Carmichael United States	46	2.5k 1.1×	1.2k 0.6×	1.8k 1.0×	1.9k 1.2×	1.7k 1.2×	196	6.4k
Marie Chupin France	31	1.6k 0.7×	1.0k 0.5×	1.4k 0.8×	866 0.5×	1.0k 0.7×	83	3.9k

Countries citing papers authored by Olivier Colliot

Since Specialization

Citations

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

Fields of papers citing papers by Olivier Colliot

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivier Colliot

This figure shows the co-authorship network connecting the top 25 collaborators of Olivier Colliot. A scholar is included among the top collaborators of Olivier Colliot 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 Olivier Colliot. Olivier Colliot 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

Varoquaux, Gaël, et al.. (2025). Confidence intervals for performance estimates in brain MRI segmentation. Medical Image Analysis. 103. 103565–103565. 3 indexed citations

Bottani, Simona, Elina Thibeau–Sutre, Sébastian Ströer, et al.. (2024). Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI. BMC Medical Imaging. 24(1). 67–67. 2 indexed citations

Colliot, Olivier, et al.. (2024). Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET. arXiv (Cornell University). 2(Generative Models). 611–656. 1 indexed citations

Faouzi, Johann, Manuela Tan, Suzanne Lesage, et al.. (2024). Proxy-analysis of the genetics of cognitive decline in Parkinson’s disease through polygenic scores. npj Parkinson s Disease. 10(1). 8–8. 5 indexed citations

Chougar, Lydia, et al.. (2024). Projected pooling loss for red nucleus segmentation with soft topology constraints. Journal of Medical Imaging. 11(4). 44002–44002. 2 indexed citations

Bottani, Simona, Ninon Burgos, Dario Saracino, et al.. (2023). Evaluation of MRI-based machine learning approaches for computer-aided diagnosis of dementia in a clinical data warehouse. Medical Image Analysis. 89. 102903–102903. 8 indexed citations

Bottani, Simona, et al.. (2023). Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data. Medical Image Analysis. 93. 103073–103073. 9 indexed citations

Thibeau–Sutre, Elina, Jelmer M. Wolterink, Olivier Colliot, & Ninon Burgos. (2023). How can data augmentation improve attribution maps for disease subtype explainability. HAL (Le Centre pour la Communication Scientifique Directe). 81–81. 1 indexed citations

Becker, E., Dario Saracino, Daisy Rinaldi, et al.. (2022). Disease Progression Score Estimation From Multimodal Imaging and MicroRNA Data Using Supervised Variational Autoencoders. IEEE Journal of Biomedical and Health Informatics. 26(12). 6024–6035. 10 indexed citations

10.

Xicota, Laura, Beata Gyorgy, Benjamin Grenier‐Boley, et al.. (2022). Association of APOE -Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults. Neurology. 99(5). e462–e475. 8 indexed citations

11.

Faouzi, Johann, Fanny Artaud, Alexis Elbaz, et al.. (2022). Machine Learning-Based Prediction of Impulse Control Disorders in Parkinson’s Disease From Clinical and Genetic Data. IEEE Open Journal of Engineering in Medicine and Biology. 3. 96–107. 4 indexed citations

12.

Bottani, Simona, et al.. (2020). Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(9). 3196–3213. 2 indexed citations

13.

Wen, Junhao, Jorge Samper‐Gonzàlez, Simona Bottani, et al.. (2020). Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer’s Disease. Neuroinformatics. 19(1). 57–78. 17 indexed citations

14.

Bône, Alexandre, et al.. (2020). Learning the spatiotemporal variability in longitudinal shape data sets. International Journal of Computer Vision. 128(12). 2873–2896. 8 indexed citations

15.

Guillon, Jérémy, Mario Chávez, Federico Battiston, et al.. (2019). Disrupted core-periphery structure of multimodal brain networks in Alzheimer’s disease. Network Neuroscience. 3(2). 635–652. 18 indexed citations

16.

Bertoux, Maxime, Julien Lagarde, Fabian Corlier, et al.. (2019). Sulcal morphology in Alzheimer's disease: an effective marker of diagnosis and cognition. Neurobiology of Aging. 84. 41–49. 24 indexed citations

17.

Querin, Giorgia, Peter Bede, Mohamed Mounir El Mendili, et al.. (2019). Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study. Annals of Neurology. 86(2). 158–167. 65 indexed citations

18.

Guillon, Jérémy, Yohan Attal, Olivier Colliot, et al.. (2016). Loss of inter-frequency brain hubs in Alzheimer's disease. arXiv (Cornell University). 2 indexed citations

19.

Colle, Romain, Olivier Colliot, Patrick Hardy, et al.. (2016). Smaller hippocampal volumes predict lower antidepressant response/remission rates in depressed patients: A meta-analysis. The World Journal of Biological Psychiatry. 19(5). 360–367. 38 indexed citations

20.

Colliot, Olivier, Lorraine Hamelin, & Marianne Sarazin. (2013). Magnetic resonance imaging for diagnosis of early Alzheimer's disease. Revue Neurologique. 169(10). 724–728. 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.

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