54 citations · 75 across the 4 of their papers we have counts for
5 papers
Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge
Alain Lalande, Zhihao Chen, Thibaut Pommier +30
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization the…
Learning With Context Feedback Loop for Robust Medical Image Segmentation
Kibrom Berihu Girum, Gilles Créhange, Alain Lalande
Deep learning has successfully been leveraged for medical image segmentation. It employs convolutional neural networks (CNN) to learn distinctive image features from a defined pixe…
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…
Deep generative model-driven multimodal prostate segmentation in radiotherapy
Kibrom Berihu Girum, Gilles Créhange, Raabid Hussain +2
Deep learning has shown unprecedented success in a variety of applications, such as computer vision and medical image analysis. However, there is still potential to improve segment…
3D landmark detection for augmented reality based otologic procedures
Raabid Hussain, Alain Lalande, Kibrom Berihu Girum +2
Ear consists of the smallest bones in the human body and does not contain significant amount of distinct landmark points that may be used to register a preoperative CT-scan with th…