Pierre-Marc Jodoin

Financement

• Subvention. Deep Learning Echocardiographic Image Analysis for the Assessment of Cardiac Pathologies. Mitacs (Vancouver, Canada). 240 000 $. (2025-2028).
• Subvention. Fully-automatic, self-corrective, and explainable echocardiographic image analysis. Natural Sciences and Engineering Research Council (Ottawa, Canada). 41 000 $. (2023-2024).
  Numéro de subvention : RGPIN-2023-04584. Voir plus
• Subvention. Model design for analyzing ultra-low framerate surveillance videos. Natural Sciences and Engineering Research Council (Ottawa, Canada). 123 000 $. (2018-2021).
  Numéro de subvention : RGPIN-2018-05401. Voir plus
• Subvention. Development of deep segmentation methods applied to satellite imagery. Natural Sciences and Engineering Research Council (Ottawa, Canada). 25 000 $. (2017-2018).
  Numéro de subvention : 521746-2017. Voir plus
• Subvention. One-Shot Traffic Analytics. Natural Sciences and Engineering Research Council (Ottawa, Canada). 25 000 $. (2015-2016).
  Numéro de subvention : 490789-2015. Voir plus
• Subvention. Classification automatique des défauts de bois de structure. Natural Sciences and Engineering Research Council (Ottawa, Canada). 25 000 $. (2015-2016).
  Numéro de subvention : 491599-2015. Voir plus
• Subvention. Méthodes avancées pour l'analyse statistique des symptômes liées aux commotions cérébrales. Natural Sciences and Engineering Research Council (Ottawa, Canada). 25 000 $. (2014-2015).
  Numéro de subvention : 470157-2014. Voir plus
• Subvention. Analyse de contenu et détection d'anomalies pour des applications en surveillance vidéo et imagerie médicale. Natural Sciences and Engineering Research Council (Ottawa, Canada). 100 000 $. (2013-2018).
  Numéro de subvention : 349975-2013. Voir plus
• Subvention. Segmentation et analyse vidéo: détection de comportement suspects. Natural Sciences and Engineering Research Council (Ottawa, Canada). 85 000 $. (2008-2013).
  Numéro de subvention : grant.2937796. Voir plus
• Subvention. PGSB. Natural Sciences and Engineering Research Council (Ottawa, Canada). 21 796 $. (2003-2004).
  Numéro de subvention : grant.2853728. Voir plus
• Subvention. PGSB. Natural Sciences and Engineering Research Council (Ottawa, Canada). 19 100 $. (2002-2003).
  Numéro de subvention : grant.2960705. Voir plus
• Subvention. PGSA. Natural Sciences and Engineering Research Council (Ottawa, Canada). 17 300 $. (2001-2002).
  Numéro de subvention : grant.2805699. Voir plus
• Subvention. PGSA/ESA. Natural Sciences and Engineering Research Council (Ottawa, Canada). 17 300 $. (2000-2001).
  Numéro de subvention : grant.2798698. Voir plus

Publications

Articles

• P.-M. Jodoin, M. Edde, G. Girard, F. Dumais, G. Theaud, M. Dumont, J.-C. Houde, Y. David, M. Descoteaux. (2025). ComBAT Harmonization for Diffusion MRI: Challenges and Best Practices. Nature Scientific Reports.
• A. A. Tasken, T. Judge, E. Andreas R. Berg, J. Yu, B. Grenne, F. Lindseth, S. Aakhus, P.-M. Jodoin, N. Duchateau, O. Bernard, G. Kiss. (2025). Estimation of Segmental Longitudinal Strain in Transesophageal Echocardiography by Deep Learning. IEEE Journal of Biomedical and Health Informatics.
• J. Lévesque, A. Théberge, M. Descoteaux, P.-M. Jodoin. (2025). Exploring the Robustness of TractOracle Methods in RL-based Tractography. Medical Image Analysis.
• N. Painchaud, P.-Y. Courand, P.-M. Jodoin, N. Duchateau, O. Bernard. (2025). Fusing Echocardiography Images and Medical Records for Continuous Patient Stratification. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.
• A. Judge, N. Duchateau, T. Judge, R. A. Sandler, J. Z. Sokol, C. Desrosiers, O. Bernard, P.-M. Jodoin. (2025). Reinforcement Learning for Unsupervised Domain Adaptation in Spatio-Temporal Echocardiography Segmentation. IEEE Transactions on Medical Imaging.
• O. Bernard, W. Romero, C. Bouton, C. Goujat, H. J. Ling, P.-M. Jodoin, F. Guo, C. Sheagren, G. Wright, A. Qayyum, M. Mazher, S. A. Niederer, H. Wang, X. Wu, F. Thaler, G. Plank, M. Urschler, R. M. Rosales, E. Pueyo, ... P. Croisille. (2025). The MYOSAIQ Challenge: Myocardial Segmentation with Automated Infarct Quantification. IEEE Transactions on Medical Imaging.
• Fan Zhang, Antoine Théberge, Pierre-Marc Jodoin, Maxime Descoteaux, Lauren J. O’Donnell. (2025). Think Deep in the Tractography Game: Deep Learning for Tractography Computing and Analysis. Brain Structure and Function.
• T. Judge, O. Bernard, W.-J. Cho Kim, A. Gomez, A. Chartsias, P.-M. Jodoin. (2025). Uncertainty Propagation for Echocardiography Clinical Metric Estimation via Contour Sampling. IEEE Transactions on Image Processing.
• A. Théberge, C. Desrosiers, M. Descoteaux, P.-M. Jodoin. (2024). What Matters in Reinforcement Learning for Tractography. Medical Image Analysis.
• F. Dumais, J. H. Legarreta, C. Lemaire, P. Poulin, F. Rheault, L. Petit, M. Barakovic, S. Magon, M. Descoteaux, P.-M. Jodoin. (2023). FIESTA: Autoencoders for Accurate Fiber Segmentation in Tractography. NeuroImage.
• Y. Skandarani, P.-M. Jodoin*, A. Lalande*. (2023). GANs for Medical Image Synthesis: An Empirical Study. Journal of Imaging.
• J. H. Legarreta, L. Petit, P.-M. Jodoin*, M. Descoteaux*. (2023). Generative Sampling in Tractography Using Autoencoders (GESTA). Medical Image Analysis.
• M.-A. Armenta, T. Judge, N. Painchaud, Y. Skandarani, C. Lemaire, G. G. Sanchez, P. Spino, P.-M. Jodoin. (2023). Neural Teleportation. Mathematics.
• G. Theaud, M. Edde, M. Dumont, C. Zotti, M. Zucchelli, S. Deslauriers-Gauthier, R. Deriche, P.-M. Jodoin, M. Descoteaux. (2022). DORIS: A Diffusion MRI-based 10 Tissue Class Deep Learning Segmentation Algorithm Tailored to Improve Anatomically-Constrained Tractography. Frontiers in Neuroimaging.
• N. Painchaud, N. Duchateau, O. Bernard, P.-M. Jodoin. (2022). Echocardiography Segmentation with Enforced Temporal Consistency. IEEE Transactions on Medical Imaging.
• Y. Skandarani, A. Lalande, J. Afilalo, P.-M. Jodoin. (2022). GANs in Cardiology. Canadian Journal of Cardiology.
• B. Anctil-Robitaille, A. Théberge, P.-M. Jodoin, M. Descoteaux, C. Desrosiers, H. Lombaert. (2022). Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging. Frontiers in Neuroimaging.
• A. Duran, O. Rouvière, T. Jaouen, P.-M. Jodoin*, C. Lartizien*. (2022). ProstAttention-Net: A Deep Attention Model for Prostate Cancer Segmentation by Aggressiveness in MRI Scans. Medical Image Analysis.
• P. Poulin, G. Theaud, F. Rheault, E. St-Onge, A. Bore, E. Renauld, L. de Beaumont, S. Guay, P.-M. Jodoin, M. Descoteaux. (2022). TractoInferno: A Large-Scale, Open-Source, Multi-Site Database for Machine Learning dMRI Tractography. Nature Scientific Data.
• Y. Skandarani, P.-M. Jodoin*, A. Lalande*. (2021). Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?. Algorithms.
• B. Kim, J. Dolz, P.-M. Jodoin, C. Desrosiers. (2021). Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images. IEEE Transactions on Medical Imaging.
• M.-A. Armenta, P.-M. Jodoin. (2021). The Representation Theory of Neural Networks. Mathematics.
• A. Théberge, C. Desrosiers, M. Descoteaux, P.-M. Jodoin. (2021). Track-To-Learn: A General Framework for Tractography with Deep Reinforcement Learning. Medical Image Analysis.
• J. H. Legarreta, L. Petit, F. Rheault, G. Theaud, C. Lemaire, M. Descoteaux, P.-M. Jodoin. (2021). Tractography Filtering Using Autoencoders. Medical Image Analysis. DOI
• N. Painchaud, Y. Skandarani, T. Judge, O. Bernard, A. Lalande, P.-M. Jodoin. (2020). Cardiac Segmentation with Strong Anatomical Guarantees. IEEE Transactions on Medical Imaging.
• S. Leclerc, E. Smistad, A. Østvik, F. Cervenansky, F. Espinosa, T. Espeland, E. A. R. Berg, T. Grenier, C. Lartizien, P.-M. Jodoin, L. Løvstakken, O. Bernard. (2020). LU-Net: A Multi-Task Network to Improve the Robustness of Deep Learning Segmentation in 2D Echocardiography. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.
• J. Z. Bojorquez, P.-M. Jodoin, S. Bricq, P. M. Walker, F. Brunotte, A. Lalande. (2019). Automatic Classification of Tissues on Prostate MRI Based on Relaxation Times and Support Vector Machine. PLOS ONE.
• C. Zotti, Z. Luo, A. Lalande, P.-M. Jodoin. (2019). Convolutional Neural Network with Shape Prior Applied to Cardiac MRI Segmentation. IEEE Journal of Biomedical and Health Informatics.
• S. Leclerc, E. Smistad, J. Pedrosa, A. Østvik, F. Espinosa, T. Espeland, E. A. R. Berg, P.-M. Jodoin, T. Grenier, C. Lartizien, J. Dhooge, L. Løvstakken, O. Bernard. (2019). Deep Convolutional Network for 2-D Echocardiographic Segmentation Based on an Open Large-Scale Patient Database. IEEE Transactions on Medical Imaging.
• M. Dumont, M. Roy, P.-M. Jodoin, F.-C. Morency, J.-C. Houde, Z. Xie, C. Bauer, T. A. Samad, K. R. A. Van Dijk, J. A. Goodman, M. Descoteaux. (2019). Free Water in White Matter Differentiates MCI and AD from Control Subjects. Frontiers in Aging Neuroscience.
• P. Poulin, D. Jörgens, P.-M. Jodoin*, M. Descoteaux*. (2019). Tractography and Machine Learning: Current State and Open Challenges. Magnetic Resonance Imaging.
• S. Obaid, A. Tucholka, J. Ghaziri, P.-M. Jodoin, F. Morency, M. Descoteaux, A. Bouthillier, D. K. Nguyen. (2018). Cortical Thickness Analysis in Operculo-Insular Epilepsy. NeuroImage: Clinical.
• O. Bernard, A. Lalande, C. Zotti, F. Cervenansky, X. Yang, P.-A. Heng, I. Cetin, K. Lekadir, O. Camara, M. A. Gonzalez-Ballester, G. Sanroma, S. Napel, S. Petersen, G. Tziritas, E. Grinias, M. Khened, V. A. Kollerathu, G. Krishnamurthi, M.-M. Rohé, ... P.-M. Jodoin. (2018). Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?. IEEE Transactions on Medical Imaging.
• Z. Luo, F. B. Charron, C. Lemaire, J. Konrad, S. Li, A. Mishra, A. Achkar, J. Eichel, P.-M. Jodoin. (2018). MIO-TCD: A New Benchmark Dataset for Vehicle Classification and Localization. IEEE Transactions on Image Processing.
• Z. Luo, P.-M. Jodoin, S.-Z. Su, S. Li, H. Larochelle. (2018). Traffic Analytics with Low Frame Rate Videos. IEEE Transactions on Circuits and Systems for Video Technology.
• M. Cousineau, P.-M. Jodoin, F. Morency, V. Rozanski, M. GrandMaison, B. J. Bedell, M. Descoteaux. (2017). A Test-Retest Study on Parkinson's PPMI Dataset Yields Statistically Significant White Matter Fascicles. NeuroImage: Clinical.
• M. Havaei, A. Davy, D. Warde-Farley, A. Biard, A. Courville, Y. Bengio, C. Pal, P.-M. Jodoin, H. Larochelle. (2017). Brain Tumor Segmentation with Deep Neural Networks. Medical Image Analysis.
• P.-M. Jodoin, L. Maddalena, A. Petrosino, Y. Wang. (2017). Extensive Benchmark and Survey of Background Modeling Methods. IEEE Transactions on Image Processing.
• M. Bernier, P.-M. Jodoin, O. Humbert, A. Lalande. (2017). Graph Cut-Based Method for Segmenting the Left Ventricle from MRI or Echocardiographic Images. Computerized Medical Imaging and Graphics.
• Y. Wang, S. Piérard, S.-Z. Su, P.-M. Jodoin. (2017). Improving Pedestrian Detection Using Motion-Guided Filtering. Pattern Recognition Letters.
• Y. Wang, Z. Luo, P.-M. Jodoin. (2017). Interactive Deep Learning Method for Segmenting Moving Objects. Pattern Recognition Letters.
• O. Maier, others. (2017). SLES 2015 -- A Public Evaluation Benchmark for Ischemic Stroke Lesion Segmentation from Multispectral MRI. Medical Image Analysis.
• L.-C. Geng, P.-M. Jodoin, S.-Z. Su, S. Z. Li. (2016). CBDF: Compressed Binary Discriminative Feature. Neurocomputing.
• G. Cañas Castañón, M.-A. Elgharib, V. Saligrama, P.-M. Jodoin. (2016). Retrieval in Long Surveillance Videos Using User-Described Motion and Object Attributes. IEEE Transactions on Circuits and Systems for Video Technology.
• O. Bernard, others. (2016). Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography. IEEE Transactions on Medical Imaging.
• M. Havaei, H. Larochelle, P. Poulin, P.-M. Jodoin. (2016). Within-Brain Classification for Brain Tumor Segmentation. International Journal of Computer Assisted Radiology and Surgery.
• C. Presseau, P.-M. Jodoin*, M. Descoteaux*. (2015). A New Compression Format for Fiber Tracking Datasets. NeuroImage.
• J. Boisvert, M.-A. Drouin, P.-M. Jodoin. (2015). High-Speed Transition Patterns for Video Projection, 3D Reconstruction, and Copyright Protection. Pattern Recognition.
• P.-M. Jodoin, F. Pinheiro, F. Oudot, A. Lalande. (2015). Left-Ventricle Segmentation of SPECT Images of Rats. IEEE Transactions on Biomedical Engineering.
• D. Zhang, P.-M. Jodoin, C. Li, G. Cai, Y. Wu. (2015). Novel Graph Cuts Method for Multi-Frame Super Resolution. IEEE Signal Processing Letters.
• N. Goyette, P.-M. Jodoin, F. Porikli, J. Konrad, P. Ishwar. (2014). A Novel Dataset for Change Detection Benchmarking. IEEE Transactions on Image Processing.
• G. Cai, P.-M. Jodoin, S. Li, Y.-D. Wu, S.-Z. Su, Z.-K. Huang. (2013). Perspective SIFT: An Efficient Tool for Low-Altitude Remote Sensing Image Registration. Signal Processing.
• A. Adam-Duquette, P.-M. Jodoin, O. Bouchot, A. Lalande. (2012). 3D Segmentation of Abdominal Aorta from CT-Scan and MR Images. Computerized Medical Imaging and Graphics.
• P.-M. Jodoin, V. Saligrama, J. Konrad. (2012). Behavior Subtraction. IEEE Transactions on Image Processing.
• M.-A. Drouin, P.-M. Jodoin, J. Prémont. (2012). Camera-Projector Matching Using Unstructured Video. Machine Vision and Applications.
• Y. Benezeth, P.-M. Jodoin, V. Saligrama. (2011). Abnormality Detection Using Low-Level Co-Occurring Events. Pattern Recognition Letters.
• A. Caron, P.-M. Jodoin. (2011). Image Multi-Distortion Estimation. IEEE Transactions on Image Processing.
• V. Saligrama, J. Konrad, P.-M. Jodoin. (2010). A Statistical Approach to Video Anomaly Identification. IEEE Signal Processing Magazine.
• E. B. Ermis, P. Clarot, P.-M. Jodoin, V. Saligrama. (2010). Activity Matching in Distributed Camera Networks. IEEE Transactions on Image Processing.
• Y. Benezeth, P.-M. Jodoin, B. Emile, H. Laurent, C. Rosenberger. (2010). Comparative Study of Background Subtraction Algorithms. Journal of Electronic Imaging.
• M. McHugh, J. Konrad, V. Saligrama, P.-M. Jodoin. (2009). Foreground-Adaptive Background Subtraction. IEEE Signal Processing Letters.
• P.-M. Jodoin, M. Mignotte. (2009). Optical-Flow Based on an Edge-Avoidance Procedure. Computer Vision and Image Understanding.
• P.-M. Jodoin, M. Mignotte, C. Rosenberger. (2007). Segmentation Framework Based on a Label Field Fusion. IEEE Transactions on Image Processing.
• P.-M. Jodoin, M. Mignotte, J. Konrad. (2007). Statistical Background Subtraction Methods Using Spatial Cues. IEEE Transactions on Circuits and Systems for Video Technology.
• P.-M. Jodoin, M. Mignotte. (2006). Markovian Segmentation and Parameter Estimation on Graphics Hardware. Journal of Electronic Imaging.
• V. Ostromoukhov, C. Donohue, P.-M. Jodoin. (2004). Fast Hierarchical Importance Sampling with Blue Noise Properties. ACM Transactions on Graphics (SIGGRAPH).

Chapitres de livre

• P.-M. Jodoin, C. Desrosiers. (2020). From Machine Learning to Deep Learning: The Basics. —.
• M. Havaei, N. Guizard, H. Larochelle, P.-M. Jodoin. (2016). Deep Learning Trends for Focal Brain Pathology Segmentation in MRI. Machine Learning for Health Informatics: State-of-the-Art and Future Challenges.
• P.-M. Jodoin, M. Van Droogenbroeck, S. Piérard, Y. Wang. (2014). Overview and Benchmarking of Motion Detection Methods. Background Modeling and Foreground Detection for Video Surveillance.
• E. Ermis, V. Saligrama, P.-M. Jodoin. (2012). Information Fusion and Anomaly Detection with Uncalibrated Cameras in Video Surveillance. Multimedia Information Extraction: Advances in Video, Audio, and Imagery Analysis for Search, Data Mining, Surveillance, and Authoring.
• Y. Benezeth, P.-M. Jodoin, V. Saligrama. (2011). Modeling Patterns of Activity and Detecting Abnormal Events with Low-Level Co-Occurences. Distributed Video Sensor Networks.

Articles de conférence

• A. Théberge, P.-M. Jodoin, J. Yuan-Mou Yang, M. Descoteaux, F. Rheault. (2025). BundleParc: Automatic Bundle Parcellation in Tumor Data. Proc. International Society for Tractography (IST).
• T. Judge, N. Duchateau, K. Faraz, P.-M. Jodoin, O. Bernard. (2025). Generation of Realistic Cardiac Ultrasound Sequences with Ground Truth Motion and Speckle Decorrelation. Proc. IEEE International Ultrasonics Symposium (IUS).
• M. Roy, J.-R. Bélanger, G. Girard, M. Edde, M. Dumont, J.-C. Houde, P.-M. Jodoin*, M. Descoteaux*. (2025). Harmonization of Diffusion MRI Measures Is Crucial for White Matter Tract Assessment in ADNI. Proc. ISMRM Diffusion Study Group Workshop.
• C. Goujat, P.-M. Jodoin, L. Boussel, O. Bernard. (2025). How Sensitive Is Performance to BB Placement Accuracy?. Proc. MICCAI-STACOM.
• A. Judge, T. Judge, N. Duchateau, J. Z. Sokol, R. A. Sandler, O. Bernard, P.-M. Jodoin. (2024). Domain Adaptation of Echocardiography Segmentation via Reinforcement Learning. Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI).
• T. Judge, O. Bernard, W.-J. Kim, A. Gomez, A. Chartsias, P.-M. Jodoin. (2024). Propagating Uncertainty from Predictions to Clinical Parameters. Proc. IEEE International Symposium on Biomedical Imaging (ISBI).
• A. Théberge, M. Descoteaux, P.-M. Jodoin. (2024). TractOracle: Towards an Anatomically-Informed Reward Function for RL-Based Tractography. Proc. MICCAI.
• T. Judge, O. Bernard, W.-J. Cho Kim, A. Gomez, A. Chartsias, P.-M. Jodoin. (2023). Asymmetric Contour Uncertainty Estimation for Medical Image Segmentation. Proc. MICCAI.
• H. J. Ling, N. Painchaud, P.-Y. Courand, P.-M. Jodoin, D. Garcia, O. Bernard. (2023). Extraction of Volumetric Indices from Echocardiography: Which Deep Learning Solution for Clinical Use?. Proc. Functional Imaging and Modeling of the Heart (FIMH).
• B. N. Kim, J. Dolz, P.-M. Jodoin, C. Desrosiers. (2023). Mixup-Privacy: A Simple yet Effective Approach for Privacy-Preserving Segmentation. Proc. Information Processing in Medical Imaging (IPMI).
• J. H. Legarreta, L. Petit, P.-M. Jodoin*, M. Descoteaux*. (2023). Trading Streamlines in Tractography Using Autoencoders (TINTA). Proc. ISMRM & ISMRT.
• T. Judge, A. Judge, P.-M. Jodoin. (2022). Anatomically Constrained Semi-Supervised Learning for Echocardiography Segmentation. Proc. Medical Imaging with Deep Learning (MIDL).
• T. Judge, O. Bernard, M. Porumb, A. Chartsias, A. Beqiri, P.-M. Jodoin. (2022). CRISP: Reliable Uncertainty Estimation for Medical Image Segmentation. Proc. MICCAI.
• J. H. Legarreta, L. Petit, P.-M. Jodoin*, M. Descoteaux*. (2022). Clustering in Tractography Using Autoencoders (CINTA). Proc. MICCAI - CDMRI Workshop.
• A. Théberge, C. Poirier, M. Descoteaux*, P.-M. Jodoin*. (2022). Incorporating Anatomical Priors into Track-to-Learn. Proc. ISMRM Diffusion Workshop.
• A. Théberge, P.-M. Jodoin*, M. Descoteaux*. (2022). The Dos and Don’ts of Reinforcement Learning for Tractography. Proc. MIDL.
• J. H. Legarreta, L. Petit, P.-M. Jodoin*, M. Descoteaux*. (2022). You Only Autoencode Once. Proc. ISMRM Diffusion Workshop.
• B. Kim, J. Dolz, C. Desrosiers, P.-M. Jodoin. (2021). Privacy Preserving for Medical Image Analysis via Non-Linear Deformation Proxy. Proc. British Machine Vision Conference (BMVC).
• A. Théberge, C. Desrosiers, M. Descoteaux, P.-M. Jodoin. (2021). Track-To-Learn: A General Framework for Tractography with Deep Reinforcement Learning. Proc. International Society for Magnetic Resonance in Medicine (ISMRM).
• A. Essemlali, E. St-Onge, J.-C. Houde, M. Descoteaux, P.-M. Jodoin. (2020). Alzheimer’s Disease Classification Using CNN over Structural Connectomes. Proc. Medical Imaging with Deep Learning (MIDL).
• Y. Skandarani, N. Painchaud, P.-M. Jodoin, A. Lalande. (2020). On the Effectiveness of GAN-Generated Cardiac MRIs for Segmentation. Proc. MIDL.
• A. Duran, P.-M. Jodoin, C. Lartizien. (2020). Prostate Cancer Semantic Segmentation by Gleason Score Group in mp-MRI with Self-Attention Model on the Peripheral Zone. Proc. MIDL.
• N. Painchaud, Y. Skandarani, T. Judge, O. Bernard, A. Lalande, P.-M. Jodoin. (2019). Cardiac MRI Segmentation with Strong Anatomical Guarantees. Proc. MICCAI.
• S. Leclerc, E. Smistad, A. Østvik, F. Espinosa, T. Espeland, E. A. R. Berg, P.-M. Jodoin, T. Grenier, C. Lartizien, L. Løvstakken, O. Bernard. (2019). Deep Learning Segmentation in 2D Echocardiography Using the CAMUS Dataset: Automatic Assessment of the Anatomical Shape Validity. Proc. MIDL.
• S. Leclerc, E. Smistad, T. Grenier, C. Lartizien, A. Østvik, F. Cervenansky, F. Espinosa, T. Espeland, E. A. R. Berg, P.-M. Jodoin, L. Løvstakken, O. Bernard. (2019). RU-Net: A Refining Segmentation Network for 2D Echocardiography. Proc. IEEE International Ultrasonics Symposium (IUS).
• F. Branchaud-Charron, A. Achkar, P.-M. Jodoin. (2019). Spectral Metric for Dataset Complexity Assessment. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
• C. Lemaire, A. Achkar, P.-M. Jodoin. (2019). Structured Pruning of Neural Networks with Budget-Aware Regularization. Proc. CVPR.
• P. Poulin, F. Rheault, E. St-Onge, P.-M. Jodoin, M. Descoteaux. (2018). Bundle-Wise Deep Tracker: Learning to Track Bundle-Specific Streamline Paths. Proc. ISMRM.
• S. Leclerc, E. Smistad, T. Grenier, C. Lartizien, A. Østvik, F. Espinosa, P.-M. Jodoin, L. Løvstakken, O. Bernard. (2018). Deep Learning Applied to Multi-Structure Segmentation in 2D Echocardiography: Preliminary Investigation of Required Database Size. Proc. IEEE International Ultrasonics Symposium (IUS).
• M. Dumont, K. Van Dijk, F.-C. Morency, J.-C. Houde, P.-M. Jodoin, Z. Xie, C. Bauer, T. Samad, M. Descoteaux, J. Goodman. (2018). White Matter Free Water Content Analysis in Different Stages of Alzheimer’s Disease. Proc. ISMRM.
• C. Zotti, Z. Luo, O. Humbert, A. Lalande, P.-M. Jodoin. (2017). GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation. Proc. MICCAI - ACDC Challenge.
• Z. Luo, A. Mishra, A. Achkar, J. Eichel, S. Li, P.-M. Jodoin. (2017). Non-Local Deep Features for Salient Object Detection. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
• F. Dutil, M. Havaei, C. Pal, H. Larochelle, P.-M. Jodoin. (2015). A Convolutional Neural Network Approach to Brain Lesion Segmentation. Proc. MICCAI - ISLES Challenge.
• M. Havaei, F. Dutil, C. Pal, H. Larochelle, P.-M. Jodoin. (2015). A Convolutional Neural Network Approach to Brain Tumor Segmentation. Proc. MICCAI - BRATS Challenge.
• E. Croteau, O. Sarrhini, S. Gascon, J. Rousseau, R. Lecomte, P.-M. Jodoin. (2015). Comparison of Semi-Automatic Cardiac Analysis Software for Left Ventricular Ejection Fraction Evaluation in Small Animal PET. Proc. Society of Nuclear Medicine and Molecular Imaging (SNMMI).
• P.-M. Jodoin, M. Mignotte, J.-F. St-Amour. (2015). Markovian Energy-Based Computer Vision Algorithms on Graphics Hardware. Proc. International Conference on Image Analysis and Processing (ICIAP).
• Y. Wang, S. Piérard, S.-Z. Su, P.-M. Jodoin. (2015). Nonlinear Background Filter to Improve Pedestrian Detection. Proc. Scene Background Modeling and Initialization (ICIP Workshop).
• Z. Luo, P.-M. Jodoin, S.-Z. Li, S.-Z. Su. (2015). Traffic Analysis Without Motion Features. Proc. IEEE International Conference on Image Processing (ICIP).
• M. Bernier, P.-M. Jodoin, A. Lalande. (2014). Automatized Evaluation of the Left Ventricular Ejection Fraction from Echocardiographic Images Using Graph Cut. Proc. MIDAS Journal — Challenge on Endocardial 3D Ultrasound Segmentation (MICCAI).
• A. Davy, M. Havaei, D. Warde-Farley, A. Biard, L. Tran, P.-M. Jodoin, A. Courville, C. Pal, H. Larochelle, Y. Bengio. (2014). Brain Tumor Segmentation with Deep Neural Networks. Proc. MICCAI — BRATS Challenge.
• Y. Wang, P.-M. Jodoin, F. Porikli, J. Konrad, Y. Benezeth, P. Ishwar. (2014). CDnet 2014: An Expanded Change Detection Benchmark Dataset. Proc. IEEE CVPR Workshop on Change Detection.
• M. Havaei, P.-M. Jodoin, H. Larochelle. (2014). Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification. Proc. International Conference on Pattern Recognition (ICPR).
• D.-X. Xia, S.-Z. Su, S. Li, P.-M. Jodoin. (2014). Lying-Pose Detection with Training Dataset Expansion. Proc. IEEE International Conference on Image Processing (ICIP).
• P.-M. Jodoin, Y. Benezeth, Y. Wang. (2013). Meta-Tracking for Video Scene Understanding. Proc. IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS).
• G. Cañas Castañón, P.-M. Jodoin, V. Saligrama. (2012). Exploratory Search of Long Surveillance Video. Proc. ACM Multimedia.
• G. Cañas Castañón, P.-M. Jodoin, V. Saligrama. (2012). Exploratory Search of Long Surveillance Video. Proc. ACM Multimedia (Demo Session).
• G. Cañas Castañón, A. Caron, P.-M. Jodoin, V. Saligrama. (2012). Real-Time Activity Search of Surveillance Video. Proc. IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS).
• J.-C. Houde, P.-M. Jodoin, F. Descĥenes. (2012). Stereoscopic Reconfiguration for 3D Displays. Proc. SPIE — Stereoscopic Displays and Applications XXIII.
• N. Goyette, P.-M. Jodoin, F. Porikli, J. Konrad, P. Ishwar. (2012). changedetection.net: A New Change Detection Benchmark Dataset. Proc. IEEE CVPR Workshop on Change Detection.
• M.-A. Drouin, P.-M. Jodoin, J. Prémont. (2010). Camera-Projector Matching Using an Unstructured Video Stream. Proc. IEEE PROCAMS.
• Y. Benezeth, P.-M. Jodoin, B. Emile, H. Laurent, C. Rosenberger. (2010). Human Detection with a Multi-Sensors Stereovision System. Proc. International Conference on Image and Signal Processing (ICISP).
• A. Caron, P.-M. Jodoin, C. Charrier. (2010). Search Strategies for Image Multi-Distortion Estimation. Proc. International Conference on Pattern Recognition (ICPR).
• Y. Benezeth, P.-M. Jodoin, V. Saligrama, C. Rosenberger. (2009). Abnormal Events Detection Based on Spatio-Temporal Co-Occurences. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
• P.-M. Jodoin, V. Saligrama, J. Konrad. (2009). Implicit Active-Contouring with MRF. Proc. International Conference on Image Analysis and Recognition (ICIAR).
• P. Clarot, E. Baki, P.-M. Jodoin, V. Saligrama. (2009). Unsupervised Camera Network Structure Estimation Based on Activity. Proc. IEEE International Conference on Distributed Smart Cameras (ICDSC).
• P.-M. Jodoin, Y. Voisin, A. Lalande, O. Bouchot, E. Steinmetz. (2008). A New Technique for Reconstructing 3D Data from IRM Images. Proc. IEEE International Conference on Image Processing (ICIP).
• E. Baki, S. Saligrama, P.-M. Jodoin, J. Konrad. (2008). Abnormal Behavior Detection and Behavior Matching for Networked Cameras. Proc. IEEE International Conference on Distributed Smart Cameras (ICDSC).
• P.-M. Jodoin, V. Saligrama, J. Konrad. (2008). Behavior Subtraction. Proc. Visual Communications and Image Processing (VCIP).
• P.-M. Jodoin, J. Konrad, V. Saligrama. (2008). Modeling Background Activity for Surveillance Applications. Proc. IEEE International Conference on Distributed Smart Cameras (ICDSC).
• M. McHugh, J. Konrad, V. Saligrama, P.-M. Jodoin, D. Castanon. (2008). Motion Detection with False Discovery Rate Control. Proc. IEEE International Conference on Image Processing (ICIP).
• P.-M. Jodoin, J. Konrad, V. Saligrama, V. Gaboury. (2008). Motion Detection with an Unstable Camera. Proc. IEEE International Conference on Image Processing (ICIP).
• E. Baki, S. Saligrama, P.-M. Jodoin, J. Konrad. (2008). Motion Segmentation and Abnormal Behavior Detection via Behavior Clustering. Proc. IEEE International Conference on Image Processing (ICIP).
• Y. Benezeth, P.-M. Jodoin, B. Emile, H. Laurent, C. Rosenberger. (2008). Review and Evaluation of Commonly-Implemented Background Subtraction Algorithm. Proc. International Conference on Pattern Recognition (ICPR).
• P.-M. Jodoin, M. Mignotte, J. Konrad. (2006). Background Subtraction Framework Based on a Local Spatial Distribution. Proc. International Conference on Image Analysis and Recognition (ICIAR).
• P.-M. Jodoin, C. Rosenberger, M. Mignotte. (2006). Detecting Half-Occlusion with a Fast Region-Based Fusion Procedure. Proc. British Machine Vision Conference (BMVC).
• P.-M. Jodoin, M. Mignotte, J. Konrad. (2006). Light et Fast Statistical Motion Detection Method Based on Ergodic Model. Proc. IEEE International Conference on Image Processing (ICIP).
• P.-M. Jodoin, M. Mignotte. (2006). Optical-Flow Based on an Edge-Avoidance Procedure. Proc. IEEE International Conference on Image Processing (ICIP).
• P.-M. Jodoin, M. Mignotte. (2005). Motion Segmentation Using a K-Nearest-Neighbor-Based Fusion Procedure of Spatial and Temporal Label Cues. Proc. International Conference on Image Analysis and Recognition (ICIAR).
• P.-M. Jodoin, J.-F. St-Amour, M. Mignotte. (2005). Unsupervised Markovian Segmentation on Graphics Hardware. Proc. International Conference on Advances in Pattern Recognition (ICAPR).
• P.-M. Jodoin, M. Mignotte. (2004). An Energy-Based Framework Using Global Spatial Constraints for the Stereo Correspondence Problem. Proc. IEEE International Conference on Image Processing (ICIP).
• M. Ĉoté, P.-M. Jodoin, C. Donohue, V. Ostromoukhov. (2004). Non-Photorealistic Rendering of Hair for Animated Cartoons. Proc. GRAPHICON.
• P.-M. Jodoin, M. Mignotte. (2004). Unsupervised Motion Detection Using a Markovian Temporal Model with Global Spatial Constraints. Proc. IEEE International Conference on Image Processing (ICIP).
• P.-M. Jodoin, V. Ostromoukhov. (2003). Halftoning Over a Hexagonal Grid. Proc. SPIE — International Society for Optical Engineering.
• P.-M. Jodoin, V. Ostromoukhov. (2002). Error-Diffusion with Blue-Noise Properties for Midtones. Proc. SPIE — International Society for Optical Engineering.
• P.-M. Jodoin, E. Epstein, M. Granger-Piché, V. Ostromoukhov. (2002). Hatching by Example: A Statistical Approach. Proc. Non-Photorealistic Animation and Rendering (NPAR).

Autres contributions

Cours enseignés ou supervisés à l'UdeS

• IFT603 - Techniques d'apprentissage. (2024-2026). (3CR).
• IFT712 - Techniques d'apprentissage. (2024-2026). (3CR).
• IFT780 - Réseaux neuronaux. (2024-2026). (3CR).
• IFT704 - Sujets choisis en intelligence artificielle. (2023). (3CR).

Divers

• G. Grenier, L. Maltais, J.-C. Houde, P.-M. Jodoin. (2024). Automatic Quality Control of Image Diffusion Processing.
• P.-M. Jodoin, M. Descoteaux. (2024). Determination of White-Matter Neurodegenerative Disease Biomarkers.
• G. Girard, M. Edde, F. Dumais, M. Dumont, G. Theaud, Y. David, J.-C. Houde, M. Descoteaux, P.-M. Jodoin. (2024). Harmonization of Diffusion MRI.
• J. Legarreta, M. Descoteaux, P.-M. Jodoin. (2022). Processing of Tractography Results Using an Autoencoder.