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20182021
most citedBenefits of Linear Conditioning with Metadata for Image Segmentation

7 citations · 12 across the 5 of their papers we have counts for

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6 papers · 1 filter

eess.IV2021

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 (…

eess.IV2021★ 1 cited

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…

eess.IV2020★ 4 cited

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…

eess.IV2020

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…

eess.IV2020

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…

eess.IV2020

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-…