10 citations · 10 across the 2 of their papers we have counts for
2 papers
eess.IV2019★ 10 cited
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…
physics.med-ph2017
Semi-automated labelling of medical images: benefits of a collaborative work in the evaluation of prostate cancer in MRI
Christian Mata, Alain Lalande, Paul Walker +2
Purpose: The goal of this study is to show the advantage of a collaborative work in the annotation and evaluation of prostate cancer tissues from T2-weighted MRI compared to the co…