Journal papers

  • 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, Submitted to Frontiers in Neuroimaging;

  • A. Theberge, C. Desrosiers, M. Descoteaux, P-M. Jodoin (2022) The Dos and Donts of Reinforcement Learning for Tractography, Submitted to Medical Image Analysis;

  • 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, 77, p.1-18;

  • P. Poulin, G. Theaud, F. Rheault, E. St-Onge, A. Bore, E. Renauld, L. de Beaumont, S. Guay. P-M Jodoin, M. Descoteaux (2021) TractoInferno: A large-scale, open-source, multi-site database for machine learning dMRI tractography, Submitted to Scientific Reports - Nature; bioRxiv 2021.11.29.470422;

  • N.Painchaud, N.Duchateau, O.Bernard, P-M Jodoin (2022) Echocardiography Segmentation with Enforced Temporal Consistency, IEEE trans. on Medical Imaging, p.1-12;

  • Y. Skandarani, A.Lalande, J. Afilalo*, P-M Jodoin* (2022) GANs in Cardiology, Canadian Journal of Cardiology 38(2), p.196–203;

  • J.H. Legaretta, L. Petit, F. Rheault, G. Theaud, C. Lemaire, M. Descoteaux*, P.-M.Jodoin* (2021) Tractography filtering using autoencoders, Elsevier Medical Image Analysis, 72, p.1-23; arXiv:2010.04007; https://doi.org/10.1016/j.media.2021.102126

  • Y. Skandarani, P-M Jodoin, A. Lalande (2021) Deep Learning based Cardiac MRI segmentation: Do we need experts?, Algorithms, 14, 212, p.1-10; arXiv:2107.11447;

  • M-A. Armenta, P-M Jodoin (2021) The Representation Theory of Neural Networks, Submitted to Mathematics, 9, 3214; arXiv:2007.12213;

  • Y. Skandarani, P-M Jodoin, A.Lalande (2021) GANs for Medical Image Synthesis: An Empirical Study, Computer Methods and Programs in Biomedicine-Update (arXiv:2105.05318);

  • M-A. Armenta, T. Judge, N. Painchaud, Y. Skandarani, C. Lemaire, G. G. Sanchez, P. Spino, P-M Jodoin (2021) Neural Teleportation, Submitted to Journal of Neural Networks; arXiv:2012.01118;

  • 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, 72, p.1-22; bioRxiv:2020.11.16.385229; https://doi.org/10.1101/2020.11.16.385229

  • 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, 40(7), p.1737-1749; arXiv:1909.04087;

  • N.Painchaud, Y.Skandarani, T.Judge, O.Bernard, A.Lalande, P-M. Jodoin (2020) Cardiac Segmentation with Strong Anatomical Guarantees, IEEE Trans. on Medical Imaging, 39(11), p.3703-3713; arXiv:2006.08825;

  • S. Leclerc, E. Smistad, A. Østvik, F. Cervenansky, F. Espinosa, T. Espeland, E. A. R. Berg, T. Grenier, C. Lartizien, P.-M. Jodoin, L. Lovstakken, and O. Bernard (2020) Lu-net: A multi-task network to improve the robustness of deep learning segmentation in 2d echocardiography, IEEE trans. on Ultrasonics, Ferroelectrics, and Frequency Control (UFFC) 67(12), p.2519-2530; arXiv:2004.02043;

  • 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, Front Aging Neuroscience, 11(270), p.1-9; biorxiv.org/content/10.1101/537092v2;

  • P. Poulin, D. Jörgens, P-M Jodoin*, M Descoteaux* (2019) Tractography and machine learning: Current state and open challenges, Magnetic Resonance Imaging (24), p.37-48; arXiv:1902.05568;

  • 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 14(2), p.1-17;

  • S. Leclerc, E Smistad, J Pedrosa, A Ostvik, F Espinosa, T. Espeland, E.A. Rye Berg, P-M. Jodoin, T. Grenier, C. Lartizien, J. Dhooge, L. Lovstakken, O. Bernard (2019) Deep convolutional network for 2-D echocardiographic segmentation based on an open large-scale patient database, IEEE transactions on Medical Imaging, 38(9), p.p.2198-2210; arXiv:1908.06948v2;

  • 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, 23(3), p.1119-1128;

  • 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, 27(10), p.5129-5141;

  • 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, X. Pennec, M. Sermesant, F. Isensee, P. Jager, K.H. Maier-Hein, C.F. Baumgartner, L.M. Koch, J.M. Wolterink, I. Isgum, Y. Jang, Y. Hong, J. Patravali, S. Jain, O. Humbert, 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, 37(11), p.p.2514-2525;

  • 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, 19, p.727-733;

  • Luo Z, Jodoin P-M, Su S-Z, Li S, Larochelle H (2018) Traffic Analytics with Low Frame Rate Videos, IEEE Transactions on Circuits and Systems for Video Technology, 28(4), p.878-891;

  • Cousineau M., Jodoin P-M, Morency F., Rozanski V., GrandMaison M., Bedell B.J., Descoteaux M. (2017) A Test-Retest Study on Parkinsons PPMI Dataset Yields Statistically Significant White Matter Fascicles, NeuroImage Clinical, 16, p.222-233;

  • Jodoin P-M, Maddaelena L., Petrosino A., Wang Y. (2017) Extensive Benchmark and Survey of Background Modeling Methods, IEEE Transactions on Image Processing, 26(11), p.5244-5256;

  • Bernier M., Jodoin P-M, Humbert O., Lalande A. (2017) Graph Cut-Based Method for Segmenting the Left Ventricle from MRI or Echocardiographic Images, Computerized medical imaging and graphics, 58, p.1-12;

  • Havaei M., Davy A., Warde-Farley D., Biard A., Courville A., Bengio Y., Pal C., Jodoin P-M, Larochelle H. (2017) Brain Tumor Segmentation with Deep Neural Networks, Medical Image Analysis, Vol 35, p.18-31;

  • Maier O. et al. (2017) SLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI, Medical Image Analysis, Vol 35, p.250-269;

  • Wang Y., Piérard S., Su S-Z., Jodoin P-M (2017) Improving pedestrian detection using motion-guided filtering, Pattern Recognition Letters, 96, p.106-112;

  • Wang Y, Luo Z., Jodoin P-M (2017) Interactive Deep Learning Method for Segmenting Moving Objects, Pattern Recognition Letters, 96, p.66-75;

  • Castanon G, Elgharib M-A, Saligrama V, Jodoin P-M. (2016) Retrieval in Long Surveillance Videos using User-Described Motion & Object Attributes, IEEE Transactions on Circuits and Systems for Video Technology, 26(12), p.2313 - 2327;

  • Havaei M., Larochelle H., Poulin P., Jodoin P-M. (2016) Within-Brain Classification for Brain Tumor Segmentation, International Journal of Computer Assisted Radiology and Surgery, 11(5), p.777-788;

  • Bernard O. et al. (2016) Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography., IEEE Transactions on Medical Imaging, 35(4), p.967-977;

  • Geng L-C, Jodoin P-M, Su S-Z., Li S.Z (2016) CBDF: Compressed Binary Discriminative Feature, Neurocomputing, 184(5), p.43-54;

  • Zhang D., Jodoin P-M, Li C., Cai G, Wu Y. (2015) Novel Graph cuts Method for Multi-Frame Super Resolution , IEEE Signal Processing Letters. 22(12), p.2279-2283;

  • Jodoin P-M, Pinheiro F., Oudot F., Lalande A. (2015) Left-Ventricle Segmentation of SPECT Images of Rats, IEEE Transactions on Biomedical Engineering, 62(9), p.2260 - 2268;

  • Presseau C., Jodoin P-M, Descoteaux M. (2015) A New Compression Format for Fiber Tracking Datasets, NeuroImage, 109(1), p.73-83;

  • Boisvert J, Drouin M-A., Jodoin P-M. (2015) High-speed Transition Patterns for Video Projection, 3D Reconstruction, and Copyright Protection, Pattern Recognition, 48(3), p.720-731;

  • Goyette N, Jodoin P-M, Porikli F, Konrad J, Ishwar P. (2014) Novel Dataset for Change Detection Benchmarking, IEEE Transactions on Image Processing, 23(11), p.4663-4679;

  • Cai G, Jodoin P-M, Li S., Wu Y-D, Su S-Z, Huang Z-K (2013) Perspective SIFT: an efficient tool for low altitude remote sensing image registration, Signal Processing,93(11), p.3088-3110;

  • Jodoin P-M., Saligrama V., Konrad J. (2012) Behavior Subtraction, IEEE Transactions on Image Processing, 21(9), p.4244-4255;

  • Adam-Duquette A., Jodoin P-M, Bouchot O., and Lalande A. (2012) 3D segmentation of abdominal aorta from CT-scan and MR images. , Computerized Medical Imaging and Graphics, 36(4), p.294-303;

  • Drouin M-A., Jodoin P-M., and Prémont J. (2012) Camera-Projector Matching using Unstructured Video, Machine Vision and Applications, 23(5), p.887-902;

  • Caron A., Jodoin P-M. (2011) Image Multi-Distortion Estimation, IEEE Transactions on Image Processing,20(12), p.3442 - 3454;

  • Benezeth Y., Jodoin P-M, and Saligrama V. (2011) Abnormality Detection Using Low-Level Co-occurring Events, Pattern Recognition Letters, 32(3), p.423-431;

  • Ermis E. B., Clarot P., Jodoin P-M, and Saligrama V. (2010) Activity Matching in Distributed Camera Networks , IEEE Transactions on Image Processing,19(10), p.2595 - 2613;

  • Saligrama V., Konrad J., and Jodoin P-M. (2010) A Statistical Approach to Video Anomaly Identification, IEEE Signal Processing Magazine, 27(5), p.18-33;

  • Benezeth Y., Jodoin P.M., Emile B., Laurent H. and Rosenberger C. (2010) Comparative Study of Background Subtraction Algorithms, Journal of Electronic Imaging 19(3), p.1-12;

  • McHugh M., Konrad J., Saligrama V., and Jodoin P-M. (2009) Foreground-Adaptive Background Subtraction, IEEE Signal Process. Lett., vol. 16, p.390-393;

  • Jodoin P-M, Mignotte M. (2009) Optical-Flow Based on an Edge-Avoidance Procedure, Computer Vision and Image Understanding, 113 (4), p.511-53;

  • Jodoin P-M, Mignotte M and Rosenberger C. (2007) Segmentation Framework Based on a Label Field Fusion, IEEE Transactions on Image Processing, 16(10), p.2535-2550;

  • Jodoin P-M, Mignotte M and Konrad J. (2007) Statistical Background Subtraction Methods Using Spatial Cues, IEEE Transactions on Circuits and Systems for Video Technology, 17(12), p.1758-1763;

  • Jodoin P-M, Mignotte M (2006) Markovian Segmentation et Parameter Estimation on Graphics Hardware, Journal of Electrical Imaging, 15(3), p.330-345;

  • Ostromoukhov V., Donohue C. and Jodoin P-M. (2004) Fast Hierarchical Importance Sampling with Blue Noise Properties, SIGGRAPH, 23(3), p.488-495;

Conference papers

  • T. Judge, A. Judge, P-M Jodoin (2022) Anatomically Constrained Semi-supervised Learning for Echocardiography Segmentation, In proceedings of Medical Imaging with Deep Learning (MIDL)

  • A. Theberge, P-M Jodoin*, M.Descoteaux* (2022) The dos and donts of reinforcement learning for tractography, In proceedings of Medical Imaging with Deep Learning (MIDL)

  • B. Kim, J. Dolz, C. Desrosiers, P-M Jodoin (2021) Privacy Preserving for Medical Image Analysis via Non-Linear Deformation Proxy, In proceedings of 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, In proceedings of International Society for Magnetic Resonance in Medicine

  • A. Essemlali, E. St-Onge, J-C. Houde, M. Descoteaux, P-M. Jodoin (2020) Alzheimers disease classification using CNN over structural connectomes , In proceedings of Medical Imaging with Deep Learning (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, In proceedings of 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, In proceedings of Medical Imaging with Deep Learning (MIDL)

  • S. Leclerc, E. Smistad, T. Grenier, C. Lartizien, A. Østvik, F. Cervenansky, F. Espinosa, T. Espeland, E. A. R. Berg, P. Jodoin, L. Lovstakken, and O. Bernard (2019) Ru-net: A refining segmentation network for 2d echocardiography, In proceedings of IEEE International Ultrasonics Symposium (IUS)

  • S. Leclerc, E. Smistad, A. Ostvik, F. Cervenansky, F. Espinosa, T. Espeland, E. A. R. Berg, P.-M. Jodoin, T. Grenier, C. Lartizien, L. Lovstakken, and O. Bernard (2019) Deep learning segmentation in 2d echocardiography using the camus dataset : Automatic assessment of the anatomical shape validity, In proceedings of Medical Imaging with Deep Learning (MIDL)

  • N Painchaud, Y Skandarani, T. Judge, O. Bernard, A. Lalande, P-M Jodoin (2019) Cardiac MRI Segmentation with Strong Anatomical Guarantees, In proceedings of MICCAI

  • Branchaud-Charron F., Aachkar A., Jodoin P-M (2019) Spectral Metric for Dataset Complexity Assessment, In proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • Lemaire C., Aachkar A., Jodoin P-M (2019) Structured pruning of neural networks with budget-aware regularization, In proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • Leclerc S, Smistad E, Grenier T, Lartizien C, Ostvik A, Espinosa F, Jodoin P-M, Lovstakken L, Bernard O. (2018) Deep Learning Applied to Multi-Structure Segmentation in 2D Echocardiography: A preliminary investigation of the required database size, In proceedings of IEEE International Ultrasonics Symposium (IUS)

  • Dumont M., Van Dijk K., Morency F., Houde J-C, Jodoin P-M, Zie Z, Bauer C., Samad T., Descoteaux M. and Goodman J. (2018) White matter free water content analysis in different stages of Alzheimers disease , In proceedings of ISMRM

  • Poulin P., Rheault F., St-Onge E, Jodoin P-M, Descoteaux M. (2018) Bundle-Wise Deep Tracker: Learning to track bundle-specific streamline paths, In proceedings of ISMRM

  • Zotti C., Luo Z., Humbert O., Lalande A., Jodoin P-M (2017) GridNet with automatic shape prior registration for automatic MRI cardiac segmentation, In proceedings of MICCAI - ACDC Challenge

  • Luo Z, Mishra A, Achkar A, Eichel J, Li S-Z, Jodoin P-M (2017) Non-Local Deep Features for Salient Object Detection, In proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • Dutil F., Havaei M., Pal C., Larochelle H., Jodoin P-M. (2015) A Convolutional Neural Network Approach to Brain Lesion Segmentation, In proceedings of MICCAI - ISLES Challenge

  • Havaei M., Dutil F., Pal C., Larochelle H., Jodoin P-M. (2015) A Convolutional Neural Network Approach to Brain Tumor Segmentation, In proceedings of MICCAI - BRATS Challenge

  • Wang Y, Pierard S, Su S-Z, Jodoin P-M (2015) Nonlinear Background Filter to Improve Pedestrian Detection, In proceedings of Scene Background Modeling and Initialization (ICIP)

  • Croteau E, Sarrhini O, Gascon S, Rousseau J., Lecomte R, Jodoin P-M (2015) Comparison of semi-automatic cardiac analysis software for the evaluation of the left ventricular ejection fraction in small animal PET, In proceedings of Society of Nuclear Medicine and Molecular Imaging (SNMMI)

  • Luo Z., Jodoin P-M, Li S-Z, Su S-Z. (2015) Traffic Analysis without Motion Features, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Bernier M., Jodoin P-M, Lalande A. (2014) Automatized Evaluation of the Left Ventricular Ejection Fraction from Echocardiographic Images Using Graph Cut, In proceedings of MIDAS Journal - Challenge on Endocardial Three-dimensional Ultrasound Segmentation (MICCAI)

  • Davy A., Havaei M., Warde-Farley D., Biard A., Tran L., Jodoin P-M, Courville A, Larochelle H, Pal C, Bengio Y (2014) Brain Tumor Segmentation with Deep Neural Networks, In proceedings of MICCAI - BRATS Challenge

  • Wang Y., Jodoin P-M, Porikli F., Konrad J., Benezeth Y, Ishwar P (2014) CDnet 2014: An Expanded Change Detection Benchmark Dataset, In proceedings of IEEE CVPR change detection workshop

  • Xia D-X, Su S-Z, Li S., Jodoin P-M (2014) Lying-Pose Detection with Training Dataset Expansion, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Havaei M., Jodoin P-M, Larochelle H. (2014) Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification, In proceedings of International Conference on Pattern Recognition (ICPR)

  • Jodoin P-M, Benezeth Y, Wang Y. (2013) Meta-Tracking for Video Scene Understanding , In proceedings of IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)

  • Castanon G, Jodoin P-M, Saligrama V. (2012) Exploratory Search of Long Surveillance Video, In proceedings of ACM-Multimedia

  • Castanon G, Jodoin P-M, Saligrama V. (2012) Exploratory Search of Long Surveillance Video, In proceedings of Demo session

  • Castanon G, Caron A., Jodoin P-M, Saligrama V. (2012) Real-Time Activity Search of Surveillance Video, In proceedings of IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS)

  • Goyette N., Jodoin P-M, Porikli F., Konrad J. and Ishwar P. (2012) changedetection.net: A New Change Detection Benchmark Dataset, In proceedings of IEEE CVPR change detection workshop

  • Houde J-C, Jodoin P-M, Deschênes F. (2012) Stereoscopic reconfiguration for 3D displays, In proceedings of SPIE, Stereoscopic Displays and Applications XXIII

  • Drouin M-A., Jodoin P-M., and Prémont J. (2010) Camera-Projector Matching Using an Unstructured Video Stream, In proceedings of IEEE PROCAMS

  • Benezeth Y., Jodoin P-M. , Emile B., Laurent H., and Rosenberger C. (2010) Human detection with a multi-sensors stereovision system, In proceedings of International Conference on Image and Signal Processing (ICISP)

  • Caron A., Jodoin P-M, and Charrier C. (2010) Search Strategies for Image Multi-Distortion Estimation, In proceedings of International Conference on Pattern Recognition (ICPR)

  • Jodoin P-M, Saligrama V. Konrad J. (2009) Implicit Active-Contouring with MRF, In proceedings of International Conference on Image Analysis and Recognition (ICIAR)

  • Benezeth Y., Jodoin P.M., Saligrama V. and Rosenberger C (2009) Abnormal Events Detection Based on Spatio-Temporal Co-occurences, In proceedings of IEEE Computer Vision and Pattern Recognition (CVPR)

  • Clarot P, Baki E., Jodoin P-M., Saligrama V. (2009) Unsupervised Camera Network Structure Estimation Based on Activity, In proceedings of IEEE International Conference on Distributed Smart Cameras (ICDSC)

  • Jodoin P-M, Konrad J. and Saligrama V. (2008) Modeling Background Activity for Surveillance Applications, In proceedings of IEEE International Conference on Distributed Smart Cameras (ICDSC)

  • Baki E., Saligrama S., Jodoin P-M, Konrad J. (2008) Abnormal Behavior Detection and Behavior Matching for Networked Cameras, In proceedings of IEEE International Conference on Distributed Smart Cameras (ICDSC)

  • Benezeth Y., Jodoin P.M., Emile B., Laurent H. and Rosenberger C. (2008) Review and Evaluation of Commonly-Implemented Background Subtraction Algorithm, In proceedings of International Conference on Pattern Recognition (ICPR)

  • Baki E., Saligrama S., Jodoin P-M, Konrad J. (2008) Motion Segmentation and Abnormal Behavior Detection via Behavior Clustering, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Konrad J., Saligrama V. and Gaboury V. (2008) Motion Detection with an Unstable Camera, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • McHugh M., Konrad J., Saligrama V., Jodoin P-M, and Castanon D. (2008) Motion Detection with False Discovery Rate Control, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Voisin Y., Lalande A. and Bouchot O. Steinmetz E (2008) A new technique for reconstructing 3D data from IRM images, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Saligrama V. and Konrad J. (2008) Behavior Subtraction, In proceedings of Visual Communications and Image Processing (VCIP)

  • Jodoin P-M, Rosenberger C. and Mignotte M. (2006) Detecting Half-Occlusion with a Fast Region-Based Fusion Procedure, In proceedings of British Machine Vision Conference (BMVC)

  • Jodoin P-M, Mignotte M. and Konrad J (2006) Background Subtraction Framework Based on a Local Spatial Distribution, In proceedings of International Conference on Image Analysis and Recognition (ICIAR)

  • Jodoin P-M, Mignotte M. (2006) Optical-Flow Based on an Edge-Avoidance Procedure, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Mignotte M. and Konrad J. (2006) Light et Fast Statistical Motion Detection Method Based on Ergodic Model, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Mignotte M and St-Amour J-F (2015) Markovian Energy-Based Computer Vision Algorithms on Graphics Hardware, In proceedings of International Conference on Image Analysis and Processing (ICIAP)

  • Jodoin P-M, St-Amour J-F and Mignotte M (2005) Unsupervised Markovian Segmentation on Graphics Hardware, In proceedings of International Conference on Advances in Pattern Recognition (ICAPR)

  • Jodoin P-M, Mignotte M (2005) Motion Segmentation Using a K-nearest-Neighbor-Based Fusion Procedure of Spatial and Temporal Label Cues, In proceedings of International Conference on Image Analysis et Recognition (ICIAR)

  • Jodoin P-M, Mignotte M (2004) Unsupervised Motion Detection Using a Markovian Temporal Model with Global Spatial Constraints, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Jodoin P-M, Mignotte M (2004) An Energy-Based Framework Using Global Spatial Constraints for the Stereo Correspondence Problem, In proceedings of IEEE International Conference on Image Processing (ICIP)

  • Côté M, Jodoin P-M, Donohue C and Ostromoukhov V (2004) Non-Photorealistic Rendering of Hair for Animated Cartoons, In proceedings of GRAPHICON

  • Jodoin P-M, Ostromoukhov V (2003) Halftoning Over a Hexagonal Grid, In proceedings of SPIE International Society for Optical Engineering

  • Jodoin P-M, Epstein E, Granger-Piché M and Ostromoukhov V (2002) Hatching by Example: a Statistical Approach, In proceedings of Non-Photorealistic Animation and Rendering (NPAR)

  • Jodoin P-M and Ostromoukhov V (2002) Error-Diffusion with Blue-Noise Properties for Midtones, In proceedings of SPIE International Society for Optical Engineering

Book chapters

  • P-M Jodoin, C.Desrosiers (2020) From machine learning to deep learning: the basics, Submitted for printing;

  • 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;Springer International Publishing;LNAI 960;

  • Jodoin P-M, Van Droogenbroeck, Pierard S. Wang Y (2014) Overview and benchmarking of motion detection methods, Background Modeling and Foreground Detection for Video Surveillance, chapter 24;Chapman and Hall/CRC;

  • Ermis E, Saligrama V, and Jodoin P-M (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;Wiley;ISBN:9781118118917;

  • Benezeth Y., Jodoin P-M, and Saligrama V. (2011) Modeling Patterns of Activity and Detecting Abnormal Events with Low-Level co-Occurences, Distributed Video Sensor Networks;Springer;

Others

  • Jodoin P-M, Saligrama V. Konrad J. (2009) Behavior subtraction, a new tool for video analytics, SPIE Newsroom, Electronic Imaging & Signal Processing (http://spie.org/x2432.xml);