126 citations · 246 across the 5 of their papers we have counts for
4 papers · 1 filter
GANs for Medical Image Synthesis: An Empirical Study
Youssef Skandarani, Pierre-Marc Jodoin, Alain Lalande
Generative Adversarial Networks (GANs) have become increasingly powerful, generating mind-blowing photorealistic images that mimic the content of datasets they were trained to repl…
Automatic Myocardial Infarction Evaluation from Delayed-Enhancement Cardiac MRI using Deep Convolutional Networks
Kibrom Berihu Girum, Youssef Skandarani, Raabid Hussain +3
In this paper, we propose a new deep learning framework for an automatic myocardial infarction evaluation from clinical information and delayed enhancement-MRI (DE-MRI). The propos…
On the effectiveness of GAN generated cardiac MRIs for segmentation
Youssef Skandarani, Nathan Painchaud, Pierre-Marc Jodoin +1
In this work, we propose a Variational Autoencoder (VAE) - Generative Adversarial Networks (GAN) model that can produce highly realistic MRI together with its pixel accurate ground…
Cardiac MRI Segmentation with Strong Anatomical Guarantees
Nathan Painchaud, Youssef Skandarani, Thierry Judge +3
Recent publications have shown that the segmentation accuracy of modern-day convolutional neural networks (CNN) applied on cardiac MRI can reach the inter-expert variability, a gre…