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Pierre-Marc Jodoin

Pierre-Marc Jodoin

D-Index & Metrics

Computer Science

D-Index
46
Citations
16073
World Ranking
6668
National Ranking
263

Overview

Pierre-Marc Jodoin is affiliated with Université de Sherbrooke in Canada. Their research spans the intersecting domains of medicine and computer science, with a focus on imaging and analysis techniques relevant to healthcare.

Their recent publications highlight contributions to medical image synthesis, segmentation, and analysis. Notable papers include:

  • GANs for Medical Image Synthesis: An Empirical Study (2023), published in Journal of Imaging
  • ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans (2022), published in Medical Image Analysis
  • LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography (2020), published in IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control
  • Filtering in tractography using autoencoders (FINTA) (2021), published in Medical Image Analysis
  • Generative Adversarial Networks in Cardiology (2021), published in Canadian Journal of Cardiology

Their work has been disseminated across several publication venues, including:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control
  • Frontiers in Neuroimaging
  • MDPI (MDPI AG)

Frequent collaborators associated with their research include Maxime Descoteaux, Antoine Théberge, Christian Desrosiers, Olivier Bernard, and Jon Haitz Legarreta.

The scientist's main fields of study are Medicine and Computer Science, with significant expertise in the following subfields:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Pediatrics, Perinatology and Child Health
  • Cardiology and Cardiovascular Medicine

The specific research topics addressed in their publications cover:

  • Advanced Neuroimaging Techniques and Applications
  • Fetal and Pediatric Neurological Disorders
  • Advanced MRI Techniques and Applications
  • Medical Imaging and Analysis
  • Advanced Neural Network Applications
  • Cardiovascular Function and Risk Factors
  • Cardiac Imaging and Diagnostics

Best Publications

  • Brain tumor segmentation with Deep Neural Networks

    Mohammad Havaei;Axel Davy;David Warde-Farley;Antoine Biard

  • Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

    Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky

  • Changedetection.net: A new change detection benchmark dataset

    Nil Goyette;Pierre-Marc Jodoin;Fatih Porikli;Janusz Konrad

  • Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography

    Sarah Leclerc;Erik Smistad;Joao Pedrosa;Andreas Ostvik

  • CDnet 2014: An Expanded Change Detection Benchmark Dataset

    Yi Wang;Pierre-Marc Jodoin;Fatih Porikli;Janusz Konrad

  • Non-local Deep Features for Salient Object Detection

    Zhiming Luo;Akshaya Mishra;Andrew Achkar;Justin Eichel

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • Comparative study of background subtraction algorithms

    Yannick Benezeth;Pierre-Marc Jodoin;Bruno Emile;Hélène Laurent

  • Review and evaluation of commonly-implemented background subtraction algorithms

    Y. Benezeth;P.M. Jodoin;B. Emile;H. Laurent

  • Interactive deep learning method for segmenting moving objects

    Yi Wang;Zhiming Luo;Pierre-Marc Jodoin

  • Fast hierarchical importance sampling with blue noise properties

    Victor Ostromoukhov;Charles Donohue;Pierre-Marc Jodoin

  • Abnormal events detection based on spatio-temporal co-occurences

    Unknown

  • Abnormal events detection based on spatio-temporal co-occurences

    Y Benezeth;P.-M Jodoin;V Saligrama;C Rosenberger

  • Foreground-Adaptive Background Subtraction

    J.M. McHugh;J. Konrad;V. Saligrama;P.-M. Jodoin

  • GANs for Medical Image Synthesis: An Empirical Study.

    Youssef Skandarani;Pierre-Marc Jodoin;Alain Lalande

  • Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation

    Clement Zotti;Zhiming Luo;Alain Lalande;Pierre-Marc Jodoin

  • Video Anomaly Identification

    V Saligrama;J Konrad;P Jodoin

  • A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles.

    Martin Cousineau;Pierre-Marc Jodoin;Eleftherios Garyfallidis;Marc-Alexandre Côté

  • MIO-TCD: A new benchmark dataset for vehicle classification and localization.

    Zhiming Luo;Frederic B-Charron;Carl Lemaire;Janusz Konrad

  • Statistical Background Subtraction Using Spatial Cues

    P.-M. Jodoin;M. Mignotte;J. Konrad

  • A Convolutional Neural Network Approach to Brain Tumor Segmentation

    Mohammad Havaei;Francis Dutil;Chris Pal;Hugo Larochelle

  • Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

    Mihaela. Pop;Maxime. Sermesant

Frequent Co-Authors

Venkatesh Saligrama
Venkatesh Saligrama Boston University
Janusz Konrad
Janusz Konrad Boston University
Maxime Descoteaux
Maxime Descoteaux Université de Sherbrooke
Hugo Larochelle
Hugo Larochelle Google (United States)
Shaozi Li
Shaozi Li Xiamen University
Christian Desrosiers
Christian Desrosiers École de Technologie Supérieure
Christophe Rosenberger
Christophe Rosenberger Université de Caen Normandie
Chris Pal
Chris Pal Polytechnique Montréal
Fatih Porikli
Fatih Porikli Australian National University
Prakash Ishwar
Prakash Ishwar Boston University

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