Pierre‐Marc Jodoin

11.5k total citations · 4 hit papers
89 papers, 5.9k citations indexed

About

Pierre‐Marc Jodoin is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Pierre‐Marc Jodoin has authored 89 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Vision and Pattern Recognition, 24 papers in Radiology, Nuclear Medicine and Imaging and 18 papers in Artificial Intelligence. Recurrent topics in Pierre‐Marc Jodoin's work include Video Surveillance and Tracking Methods (32 papers), Advanced Vision and Imaging (24 papers) and Advanced Neuroimaging Techniques and Applications (16 papers). Pierre‐Marc Jodoin is often cited by papers focused on Video Surveillance and Tracking Methods (32 papers), Advanced Vision and Imaging (24 papers) and Advanced Neuroimaging Techniques and Applications (16 papers). Pierre‐Marc Jodoin collaborates with scholars based in Canada, United States and France. Pierre‐Marc Jodoin's co-authors include Hugo Larochelle, Mohammad Havaei, Janusz Konrad, Yoshua Bengio, Chris Pal, Axel Davy, Aaron Courville, David Warde-Farley, Zhiming Luo and Venkatesh Saligrama and has published in prestigious journals such as PLoS ONE, NeuroImage and IEEE Transactions on Image Processing.

In The Last Decade

Pierre‐Marc Jodoin

85 papers receiving 5.7k citations

Hit Papers

Brain tumor segmentation with Deep Neural Networks 2012 2026 2016 2021 2016 2012 2017 2023 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre‐Marc Jodoin Canada 29 4.1k 1.5k 1.4k 1.3k 603 89 5.9k
Weidong Cai Australia 38 3.0k 0.7× 2.4k 1.6× 792 0.6× 2.1k 1.6× 522 0.9× 303 7.0k
Yizhou Yu China 51 6.2k 1.5× 2.3k 1.5× 525 0.4× 1.5k 1.2× 464 0.8× 221 9.5k
Chris Pal United States 19 2.6k 0.6× 1.3k 0.9× 1.3k 0.9× 802 0.6× 440 0.7× 41 4.1k
Yefeng Zheng China 44 3.1k 0.8× 2.2k 1.5× 304 0.2× 2.1k 1.7× 1.2k 2.0× 293 6.8k
Christian Ledig United Kingdom 19 8.2k 2.0× 1.4k 0.9× 1.2k 0.8× 1.9k 1.4× 943 1.6× 43 11.7k
Vijayan K. Asari United States 28 3.0k 0.7× 1.3k 0.9× 272 0.2× 997 0.8× 450 0.7× 283 5.5k
Marc Niethammer United States 33 2.2k 0.5× 1.3k 0.9× 337 0.2× 1.7k 1.3× 590 1.0× 179 5.1k
Ghassan Hamarneh Canada 39 2.7k 0.7× 1.8k 1.2× 287 0.2× 1.9k 1.5× 1.1k 1.8× 252 6.7k
Aly A. Farag United States 30 3.4k 0.8× 699 0.5× 300 0.2× 1.0k 0.8× 535 0.9× 304 5.2k

Countries citing papers authored by Pierre‐Marc Jodoin

Since Specialization
Citations

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

Fields of papers citing papers by Pierre‐Marc Jodoin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre‐Marc Jodoin

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

All Works

20 of 20 papers shown
1.
Lévesque, Josée, et al.. (2025). Exploring the robustness of TractOracle methods in RL-based tractography. Medical Image Analysis. 106. 103743–103743.
2.
Zhang, Fan, et al.. (2025). Think deep in the tractography game: deep learning for tractography computing and analysis. Brain Structure and Function. 230(6). 100–100.
3.
Desrosiers, Christian, et al.. (2024). What matters in reinforcement learning for tractography. Medical Image Analysis. 93. 103085–103085. 2 indexed citations
4.
Skandarani, Youssef, Pierre‐Marc Jodoin, & Alain Lalande. (2023). GANs for Medical Image Synthesis: An Empirical Study. Journal of Imaging. 9(3). 69–69. 107 indexed citations breakdown →
5.
Poulin, Philippe, Guillaume Theaud, François Rheault, et al.. (2022). TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography. Scientific Data. 9(1). 725–725. 21 indexed citations
6.
St‐Onge, Etienne, et al.. (2020). Understanding Alzheimer disease’s structural connectivity through explainable AI. 217–229. 10 indexed citations
7.
Leclerc, Sarah, Erik Smistad, Andreas Østvik, et al.. (2020). LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 67(12). 2519–2530. 38 indexed citations
8.
Dumont, Matthieu, Maggie Roy, Pierre‐Marc Jodoin, et al.. (2019). Free Water in White Matter Differentiates MCI and AD From Control Subjects. Frontiers in Aging Neuroscience. 11. 270–270. 70 indexed citations
9.
Desrosiers, Christian, et al.. (2019). Privacy-Net: An Adversarial Approach For Identity-obfuscated Segmentation.. 2 indexed citations
10.
Zotti, Clément, Zhiming Luo, Alain Lalande, & Pierre‐Marc Jodoin. (2018). Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation. IEEE Journal of Biomedical and Health Informatics. 23(3). 1119–1128. 123 indexed citations
11.
Jodoin, Pierre‐Marc, Eleftherios Garyfallidis, Marc-Alexandre Côté, et al.. (2017). A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles. NeuroImage Clinical. 16. 222–233. 102 indexed citations
12.
Havaei, Mohammad, Axel Davy, David Warde-Farley, et al.. (2016). Brain tumor segmentation with Deep Neural Networks. Medical Image Analysis. 35. 18–31. 2102 indexed citations breakdown →
13.
Luo, Zhiming, Pierre‐Marc Jodoin, Shaozi Li, & Songzhi Su. (2015). Traffic analysis without motion features. 3290–3294. 22 indexed citations
14.
Jodoin, Pierre‐Marc, et al.. (2015). A new compression format for fiber tracking datasets. NeuroImage. 109. 73–83. 20 indexed citations
15.
Wang, Yi, Pierre‐Marc Jodoin, Fatih Porikli, et al.. (2014). CDnet 2014: An Expanded Change Detection Benchmark Dataset. HAL (Le Centre pour la Communication Scientifique Directe). 393–400. 21 indexed citations
16.
Jodoin, Pierre‐Marc, et al.. (2012). Changedetection.net: A new change detection benchmark dataset. ANU Open Research (Australian National University). 1–8. 578 indexed citations breakdown →
17.
Saligrama, Venkatesh, et al.. (2012). Exploratory search of long surveillance videos. 309–318. 4 indexed citations
18.
Benezeth, Yannick, Pierre‐Marc Jodoin, Bruno Emile, Hélène Laurent, & Christophe Rosenberger. (2008). Review and Evaluation of Commonly-Implemented Background Subtraction Algorithms. HAL (Le Centre pour la Communication Scientifique Directe). 1–4. 214 indexed citations
19.
Jodoin, Pierre‐Marc, Venkatesh Saligrama, & Janusz Konrad. (2007). Behavior subtraction. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6822. 68220B–68220B. 9 indexed citations
20.
Jodoin, Pierre‐Marc, Max Mignotte, & Janusz Konrad. (2006). Light and Fast Statistical Motion Detection Method Based on Ergodic Model. 1053–1056. 3 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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