Spremljaj
Florence Forbes
Florence Forbes
Director of Research, INRIA, Grenoble Rhone-Alpes
Preverjeni e-poštni naslov na inria.fr - Domača stran
Naslov
Navedeno
Navedeno
Leto
The multimodal brain tumor image segmentation benchmark (BRATS)
BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ...
IEEE transactions on medical imaging 34 (10), 1993-2024, 2014
60632014
Deviance information criteria for missing data models
G Celeux, F Forbes, CP Robert, DM Titterington
11072006
Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study
C Chen, E Durand, F Forbes, O François
Molecular Ecology Notes 7 (5), 747-756, 2007
8512007
EM procedures using mean field-like approximations for Markov model-based image segmentation
G Celeux, F Forbes, N Peyrard
Pattern recognition 36 (1), 131-144, 2003
4442003
Objective evaluation of multiple sclerosis lesion segmentation using a data management and processing infrastructure
O Commowick, A Istace, M Kain, B Laurent, F Leray, M Simon, SC Pop, ...
Scientific reports 8 (1), 13650, 2018
2592018
Rigid and articulated point registration with expectation conditional maximization
R Horaud, F Forbes, M Yguel, G Dewaele, J Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (3), 587-602, 2010
2532010
A component-wise EM algorithm for mixtures
G Celeux, S Chrétien, F Forbes, A Mkhadri
Journal of Computational and Graphical Statistics 10 (4), 697-712, 2001
1912001
Hidden Markov random field model selection criteria based on mean field-like approximations
F Forbes, N Peyrard
IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (9), 1089-1101, 2003
1682003
EM algorithms for weighted-data clustering with application to audio-visual scene analysis
ID Gebru, X Alameda-Pineda, F Forbes, R Horaud
IEEE transactions on pattern analysis and machine intelligence 38 (12), 2402 …, 2016
1522016
Partial volume estimation in brain MRI revisited. Medical Image Computing and Computer-Assisted Intervention—MICCAI 2014
A Roche, F Forbes
Springer, 2014
1402014
Acoustic space learning for sound-source separation and localization on binaural manifolds
A Deleforge, F Forbes, R Horaud
International journal of neural systems 25 (01), 1440003, 2015
1312015
Multimodal MRI segmentation of ischemic stroke lesions
Y Kabir, M Dojat, B Scherrer, F Forbes, C Garbay
2007 29th annual international conference of the IEEE engineering in …, 2007
1232007
A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: application to robust clustering
F Forbes, D Wraith
Statistics and computing 24 (6), 971-984, 2014
1212014
Distributed local MRF models for tissue and structure brain segmentation
B Scherrer, F Forbes, C Garbay, M Dojat
IEEE Transactions on Medical Imaging 28 (8), 1278-1295, 2009
922009
High-dimensional regression with gaussian mixtures and partially-latent response variables
A Deleforge, F Forbes, R Horaud
Statistics and Computing 25 (5), 893-911, 2015
912015
Fast joint detection-estimation of evoked brain activity in event-related fMRI using a variational approach
L Chaari, T Vincent, F Forbes, M Dojat, P Ciuciu
IEEE transactions on Medical Imaging 32 (5), 821-837, 2012
902012
Fully automatic brain tumor segmentation from multiple MR sequences using hidden Markov fields and variational EM
S Doyle, F Vasseur, M Dojat, F Forbes
Procs. NCI-MICCAI BraTS, 18-22, 2013
722013
Fully automatic lesion localization and characterization: Application to brain tumors using multiparametric quantitative MRI data
A Arnaud, F Forbes, N Coquery, N Collomb, B Lemasson, EL Barbier
IEEE transactions on medical imaging 37 (7), 1678-1689, 2018
572018
An improved CUDA-based implementation of differential evolution on GPU
AK Qin, F Raimondo, F Forbes, YS Ong
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
572012
Combining Monte Carlo and mean-field-like methods for inference in hidden Markov random fields
F Forbes, G Fort
IEEE transactions on image processing 16 (3), 824-837, 2007
512007
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