activity
20172021
most citedOn the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

352 citations · 541 across the 5 of their papers we have counts for

collaborators

7 papers

eess.IV202121 cited

MONAIfbs: MONAI-based fetal brain MRI deep learning segmentation

Marta B. M. Ranzini, Lucas Fidon, Sébastien Ourselin +2

In fetal Magnetic Resonance Imaging, Super Resolution Reconstruction (SRR) algorithms are becoming popular tools to obtain high-resolution 3D volume reconstructions from low-resolu…

cs.CV202153 cited

Image Compositing for Segmentation of Surgical Tools without Manual Annotations

Luis C. Garcia-Peraza-Herrera, Lucas Fidon, Claudia D'Ettorre +3

Producing manual, pixel-accurate, image segmentation labels is tedious and time-consuming. This is often a rate-limiting factor when large amounts of labeled images are required, s…

eess.IV2020

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging

Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky +37

Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised c…

eess.IV202055 cited

Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for brain tumor segmentation: BraTS 2020 challenge

Lucas Fidon, Sebastien Ourselin, Tom Vercauteren

Training a deep neural network is an optimization problem with four main ingredients: the design of the deep neural network, the per-sample loss function, the population loss funct…

eess.IV2019

Incompressible image registration using divergence-conforming B-splines

Lucas Fidon, Michael Ebner, Luis C. Garcia-Peraza-Herrera +3

Anatomically plausible image registration often requires volumetric preservation. Previous approaches to incompressible image registration have exploited relaxed constraints, ad ho…

cs.CV2017352 cited

On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

Wenqi Li, Guotai Wang, Lucas Fidon +3

Deep convolutional neural networks are powerful tools for learning visual representations from images. However, designing efficient deep architectures to analyse volumetric medical…