Lucas Fidon
Title
Cited by
Cited by
Year
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
4972018
NiftyNet: a deep-learning platform for medical imaging
E Gibson, W Li, C Sudre, L Fidon, DI Shakir, G Wang, Z Eaton-Rosen, ...
Computer methods and programs in biomedicine 158, 113-122, 2018
3522018
On the compactness, efficiency, and representation of 3D convolutional networks: brain parcellation as a pretext task
W Li, G Wang, L Fidon, S Ourselin, MJ Cardoso, T Vercauteren
IPMI 2017, 348-360, 2017
1852017
Generalised wasserstein dice score for imbalanced multi-class segmentation using holistic convolutional networks
L Fidon, W Li, LC Garcia-Peraza-Herrera, J Ekanayake, N Kitchen, ...
MICCAI Brainlesion Workshop 2017, 64-76, 2017
922017
Toolnet: holistically-nested real-time segmentation of robotic surgical tools
LC Garcia-Peraza-Herrera, W Li, L Fidon, C Gruijthuijsen, A Devreker, ...
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
712017
Scalable multimodal convolutional networks for brain tumour segmentation
L Fidon, W Li, LC Garcia-Peraza-Herrera, J Ekanayake, N Kitchen, ...
MICCAI 2017, 285-293, 2017
412017
Context Aware 3D CNNs for Brain Tumor Segmentation
S Chandra, M Vakalopoulou, L Fidon, E Battistella, T Estienne, R Sun, ...
MICCAI Brainlesion Workshop 2018, 299-310, 2018
16*2018
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
S Tilborghs*, I Dirks*, L Fidon*, S Willems*, T Eelbode*, J Bertels*, B Ilsen, ...
arXiv preprint arXiv:2007.15546, 2020
52020
PO-1002 Pseudo Computed Tomography generation using 3D deep learning–Application to brain radiotherapy
EA Andres*, L Fidon*, M Vakalopoulou, G Noël, S Niyoteka, N Benzazon, ...
Radiotherapy and Oncology 133, S553, 2019
52019
A System and Computer-Implemented Method for Segmenting an Image
G Wang, T Vercauteren, S Ourselin, W Li, L Fidon
US Patent App. 16/622,782, 2020
32020
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
AD Berenguer, H Sahli, B Joukovsky, M Kvasnytsia, I Dirks, ...
arXiv preprint arXiv:2011.11719, 2020
22020
Dosimetry-driven quality measure of brain pseudo Computed Tomography generated from deep learning for MRI-only radiotherapy treatment planning
EA Andres*, L Fidon*, M Vakalopoulou, M Lerousseau, A Carré, R Sun, ...
International Journal of Radiation Oncology Biology Physics, 2020
22020
Distributionally Robust Deep Learning using Hardness Weighted Sampling
L Fidon, S Ourselin, T Vercauteren
arXiv preprint arXiv:2001.02658, 2020
2*2020
Incompressible image registration using divergence-conforming B-splines
L Fidon, M Ebner, LC Garcia-Peraza-Herrera, M Modat, S Ourselin, ...
MICCAI 2019, 2019
22019
Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for brain tumor segmentation: BraTS 2020 challenge
L Fidon, S Ourselin, T Vercauteren
arXiv preprint arXiv:2011.01614, 2020
12020
MONAIfbs: MONAI-based fetal brain MRI deep learning segmentation
M Ranzini, L Fidon, S Ourselin, M Modat, T Vercauteren
arXiv preprint arXiv:2103.13314, 2021
2021
Image Compositing for Segmentation of Surgical Tools without Manual Annotations
LC Garcia-Peraza-Herrera, L Fidon, C D’Ettorre, D Stoyanov, ...
IEEE Transactions on Medical Imaging, 2021
2021
PH-0408: Assessment of the generalizability to pediatric protontherapy of a 3D network generating pseudo-CT
EA Andres, M Caussé, L Fidon, L Ermeneux, S Bolle, V Martin, ...
Radiotherapy and Oncology 152, S219-S220, 2020
2020
PO-1702: Optimizing the generation of brain pseudo-CT from MRI based on a highly efficient 3D neural network
EA Andres, L Fidon, M Vakalopoulou, M Lerousseau, A Carré, R Sun, ...
Radiotherapy and Oncology 152, S938-S939, 2020
2020
Min-Cut Max-Flow for Network Abnormality Detection: Application to Preterm Birth
H Irzan, L Fidon, T Vercauteren, S Ourselin, N Marlow, A Melbourne
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020
2020
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Articles 1–20