175 citations · 743 across the 29 of their papers we have counts for
16 papers · 1 filter
NeoRS: a neonatal resting state fMRI data preprocessing pipeline
V. Enguix, J. Kenley, D. Luck +2
Resting state fMRI (rsfMRI) has been shown to be a promising tool to study intrinsic functional connectivity and assess its integrity in cerebral development. In neonates, where fM…
Medical Image Segmentation on MRI Images with Missing Modalities: A Review
Reza Azad, Nika Khosravi, Mohammad Dehghanmanshadi +2
Dealing with missing modalities in Magnetic Resonance Imaging (MRI) and overcoming their negative repercussions is considered a hurdle in biomedical imaging. The combination of a s…
Label fusion and training methods for reliable representation of inter-rater uncertainty
Andreanne Lemay, Charley Gros, Enamundram Naga Karthik +1
Medical tasks are prone to inter-rater variability due to multiple factors such as image quality, professional experience and training, or guideline clarity. Training deep learning…
2D Multi-Class Model for Gray and White Matter Segmentation of the Cervical Spinal Cord at 7T
Nilser J. Laines Medina, Charley Gros, Julien Cohen-Adad +2
The spinal cord (SC), which conveys information between the brain and the peripheral nervous system, plays a key role in various neurological disorders such as multiple sclerosis (…
Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge
Uzay Macar, Enamundram Naga Karthik, Charley Gros +2
This paper gives a detailed description of the pipelines used for the 2nd edition of the MICCAI 2021 Challenge on Multiple Sclerosis Lesion Segmentation. An overview of the data pr…
Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling
Reza Azad, Lucas Rouhier, Julien Cohen-Adad
Labeling vertebral discs from MRI scans is important for the proper diagnosis of spinal related diseases, including multiple sclerosis, amyotrophic lateral sclerosis, degenerative…
Evaluation of distortion correction methods in diffusion MRI of the spinal cord
Haykel Snoussi, Julien Cohen-Adad, Olivier Commowick +6
Background: Magnetic field inhomogeneities generate important geometric distortions in reconstructed echo-planar images. Various procedures were proposed for correcting these disto…
Reproducibility and Evolution of Diffusion MRI Measurements within the Cervical Spinal Cord in Multiple Sclerosis
Haykel Snoussi, Emmanuel Caruyer, Benoit Combes +5
In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain images, this is known as the clinical-radiolo…
Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord
Haykel Snoussi, Julien Cohen-Adad, Benoit Combes +5
Multiple sclerosis is an inflammatory disorder of the central nervous system. Quantitative MRI has huge potential to provide intrinsic and normative values of tissue properties use…
Dynamic Shimming in the Cervical Spinal Cord for Multi-Echo Gradient-Echo Imaging at 3 T
E. Alonso-Ortiz, D. Papp, A. D'Astous +1
Obtaining high quality images of the spinal cord with MRI is difficult, partly due to the fact that the spinal cord is surrounded by a number of structures that have differing magn…
Multiclass Spinal Cord Tumor Segmentation on MRI with Deep Learning
Andreanne Lemay, Charley Gros, Zhizheng Zhuo +4
Spinal cord tumors lead to neurological morbidity and mortality. Being able to obtain morphometric quantification (size, location, growth rate) of the tumor, edema, and cavity can…
SoftSeg: Advantages of soft versus binary training for image segmentation
Charley Gros, Andreanne Lemay, Julien Cohen-Adad
Most image segmentation algorithms are trained on binary masks formulated as a classification task per pixel. However, in applications such as medical imaging, this "black-and-whit…
ivadomed: A Medical Imaging Deep Learning Toolbox
Charley Gros, Andreanne Lemay, Olivier Vincent +4
ivadomed is an open-source Python package for designing, end-to-end training, and evaluating deep learning models applied to medical imaging data. The package includes APIs, comman…
Spine intervertebral disc labeling using a fully convolutional redundant counting model
Lucas Rouhier, Francisco Perdigon Romero, Joseph Paul Cohen +1
Labeling intervertebral discs is relevant as it notably enables clinicians to understand the relationship between a patient's symptoms (pain, paralysis) and the exact level of spin…
Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?
Olivier Vincent, Charley Gros, Joseph Paul Cohen +1
Despite recent improvements in medical image segmentation, the ability to generalize across imaging contrasts remains an open issue. To tackle this challenge, we implement Feature-…
U-Net Fixed-Point Quantization for Medical Image Segmentation
MohammadHossein AskariHemmat, Sina Honari, Lucas Rouhier +4
Model quantization is leveraged to reduce the memory consumption and the computation time of deep neural networks. This is achieved by representing weights and activations with a l…