26 citations · 26 across the 1 of their papers we have counts for
4 papers
Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation
Reuben Dorent, Samuel Joutard, Jonathan Shapey +4
We introduce , a weakly supervised 3D approach to train a deep image segmentation network using particularly weak train-time annotations: only 6 extreme clicks…
Scribble-based Domain Adaptation via Co-segmentation
Reuben Dorent, Samuel Joutard, Jonathan Shapey +7
Although deep convolutional networks have reached state-of-the-art performance in many medical image segmentation tasks, they have typically demonstrated poor generalisation capabi…
Permutohedral Attention Module for Efficient Non-Local Neural Networks
Samuel Joutard, Reuben Dorent, Amanda Isaac +3
Medical image processing tasks such as segmentation often require capturing non-local information. As organs, bones, and tissues share common characteristics such as intensity, sha…
Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation
Reuben Dorent, Samuel Joutard, Marc Modat +2
We propose a new deep learning method for tumour segmentation when dealing with missing imaging modalities. Instead of producing one network for each possible subset of observed mo…