175 citations · 743 across the 29 of their papers we have counts for
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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-…