Loïc Le Folgoc

Microsoft Research Cambridge

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I am interested in data analysis, including machine learning, signal processing and information geometry – all that involves algorithms to automatically understand & leverage structure in complex data.

Papers25 papers

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Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Carlo Biffi,Juan J. Cerrolaza,Giacomo Tarroni,Wenjia Bai, Antonio De Marvao,Ozan Oktay,Christian Ledig,Loic Le Folgoc, Konstantinos Kamnitsas, Georgia Doumou,Jinming Duan,Sanjay K. Prasad

IEEE Transactions on Medical Imaging, pp.1-1, (2020)

Bibtex

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Carlo Biffi, Georgia Doumou,Jinming Duan,Sanjay K Prasad,Stuart A Cook,Declan P O Regan,Daniel Rueckert,Juan J Cerrolaza,Giacomo Tarroni,Wenjia Bai, Antonio De Marvao,Ozan Oktay

IEEE Transactions on Medical Imaging, no. 6 (2020): 2088-2099

Cited by2WOSEIBibtex

Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface

Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward,Loic Le Folgoc, John Cupitt,Antonios Makropoulos,Andreas Schuh,Daniel Rueckert,Amir Alansary

Bibtex

Bayesian Sampling Bias Correction: Training with the Right Loss Function

L. Le Folgoc, V. Baltatzis, A. Alansary,S. Desai,A. Devaraj,S. Ellis, O. E. Martinez Manzanera, F. Kanavati, A. Nair, J. Schnabel,B. Glocker

Bibtex

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

Monteiro Miguel,Folgoc Loïc Le,de Castro Daniel Coelho,Pawlowski Nick,Marques Bernardo,Kamnitsas Konstantinos,van der Wilk Mark,Glocker Ben

NeurIPS 2020, (2020)

Bibtex

Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling

Biffi Carlo,Cerrolaza Juan J.,Tarroni Giacomo,Bai Wenjia,Oktay Ozan,Folgoc Loic Le, Kamnitsas Konstantinos, de Marvao Antonio, Doumou Georgia,Duan Jinming,Prasad Sanjay K.,Cook Stuart A.

Cited by2Bibtex

Evaluating reinforcement learning agents for anatomical landmark detection

Amir Alansary,Ozan Oktay, Yuanwei Li,Loic Le Folgoc, Benjamin Hou, Ghislain Vaillant, Konstantinos Kamnitsas, Athanasios Vlontzos,Ben Glocker,Bernhard Kainz,Daniel Rueckert

Medical image analysis, (2019): 156-164

Cited by38WOSEIBibtex

Deep Learning for Cardiac Motion Estimation - Supervised vs. Unsupervised Training

Huaqi Qiu, Chen Qin,Loïc Le Folgoc, Benjamin Hou, Jo Schlemper,Daniel Rueckert

STACOM@MICCAI, pp.186-194, (2019)

EIBibtex

Semi-Supervised Learning via Compact Latent Space Clustering

Konstantinos Kamnitsas,Daniel Coelho De Castro,Loïc Le Folgoc, Ian Walker,Ryutaro Tanno,Daniel Rueckert,Ben Glocker,Antonio Criminisi,Aditya V. Nori

international conference on machine learning, (2018): 2464-2473

Cited by35EIBibtex

Learning Nearby Outliers with Variational Autoencoders

Jeremy Tan, Daniel C Castro,Loic Le Folgoc, Steven McDonagh,Ben Glocker, Bernhard Kainz

(2018)

Bibtex

Attention U-Net: Learning Where to Look for the Pancreas

Ozan Oktay, Jo Schlemper,Loïc Le Folgoc, Matthew C. H. Lee,Mattias P. Heinrich,Kazunari Misawa,Kensaku Mori,Steven G. McDonagh,Nils Y. Hammerla,Bernhard Kainz,Ben Glocker,Daniel Rueckert

arXiv: Computer Vision and Pattern Recognition, (2018)

Cited by394EIBibtex

Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

Amir Alansary,Loïc Le Folgoc, Ghislain Vaillant,Ozan Oktay, Yuanwei Li,Wenjia Bai,Jonathan Passerat-Palmbach,Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou,Steven G. McDonagh,Ben Glocker

MICCAI, (2018): 277-285

Cited by21EIBibtex

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Meghan W Macomber,Mark Phillips, Ivan Tarapov,Rajesh Jena,Aditya Nori, David Carter,Loic Le Folgoc,Antonio Criminisi,Matthew J Nyflot

Physics in medicine and biology, no. 23 (2018): 235002

Cited by7WOSBibtex

Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Loïc Le Folgoc,Aditya V. Nori,Antonio Criminisi

IPMI, pp.67-79, (2017)

Cited by3EIBibtex

Quantifying Registration Uncertainty With Sparse Bayesian Modelling

Loïc Le Folgoc,Hervé Delingette,Antonio Criminisi,Nicholas Ayache

IEEE Transactions on Medical Imaging, no. 2 (2017): 607-617

Cited by23EIWOSBibtex

Autosegmentation of Prostate Anatomy for Radiation Treatment Planning Using Machine Learning Models of Radiomic Features: SU F FS4 08

M Macomber, M Phillips, I Tarapov, A Nori, D Carter,L Le Folgoc, A Criminisi, M Nyflot

Medical Physics, no. 6 (2017)

Bibtex

Lifted Auto-Context Forests for Brain Tumour Segmentation

Loïc Le Folgoc,Aditya V. Nori, Siddharth Ancha,Antonio Criminisi

BrainLes@MICCAI, pp.171-183, (2016)

Cited by16EIBibtex

Statistical learning for image-based personalization of cardiac models. (Apprentissage statistique pour la personnalisation de modèles cardiaques à partir de données d'imagerie)

Loïc Le Folgoc

(2015)

EIBibtex

Local late gadolinium enhancement features to identify the electrophysiological substrate of post-infarction ventricular tachycardia: a machine learning approach

Rocio Cabrera Lozoya,Jan Margeta,Loic Le Folgoc,Yuki Komatsu,Benjamin Berte,Jatin Relan,Hubert Cochet,Michel Haissaguerre,Pierre Jais,Nicholas Ayache,Maxime Sermesant

Journal of Cardiovascular Magnetic Resonance, no. S1 (2015): P234

Cited by3Bibtex

Sparse Bayesian Registration of Medical Images for Self-Tuning of Parameters and Spatially Adaptive Parametrization of Displacements

Loic Le Folgoc,Herve Delingette,Antonio Criminisi,Nicholas Ayache

Medical Image Analysis, (2015)

Cited by17EIWOSBibtex

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