Caroline Petitjean
Caroline Petitjean
LITIS EA 4108, Université de Rouen, France
Potvrđena adresa e-pošte na - Početna stranica
A dataset for breast cancer histopathological image classification
FA Spanhol, LS Oliveira, C Petitjean, L Heutte
Ieee transactions on biomedical engineering 63 (7), 1455-1462, 2015
Breast cancer histopathological image classification using convolutional neural networks
FA Spanhol, LS Oliveira, C Petitjean, L Heutte
2016 international joint conference on neural networks (IJCNN), 2560-2567, 2016
A review of segmentation methods in short axis cardiac MR images
C Petitjean, JN Dacher
Medical image analysis 15 (2), 169-184, 2011
Medical image synthesis with context-aware generative adversarial networks
D Nie, R Trullo, J Lian, C Petitjean, S Ruan, Q Wang, D Shen
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
Medical image synthesis with deep convolutional adversarial networks
D Nie, R Trullo, J Lian, L Wang, C Petitjean, S Ruan, Q Wang, D Shen
IEEE Transactions on Biomedical Engineering 65 (12), 2720-2730, 2018
Multiple instance learning for histopathological breast cancer image classification
PJ Sudharshan, C Petitjean, F Spanhol, LE Oliveira, L Heutte, P Honeine
Expert Systems with Applications 117, 103-111, 2019
Deep features for breast cancer histopathological image classification
FA Spanhol, LS Oliveira, PR Cavalin, C Petitjean, L Heutte
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017
Right ventricle segmentation from cardiac MRI: a collation study
C Petitjean, MA Zuluaga, W Bai, JN Dacher, D Grosgeorge, J Caudron, ...
Medical image analysis 19 (1), 187-202, 2015
Assessment of myocardial function: a review of quantification methods and results using tagged MRI
C Petitjean, N Rougon, P Cluzel
Journal of Cardiovascular Magnetic Resonance 7 (2), 501-516, 2005
One class random forests
C Désir, S Bernard, C Petitjean, L Heutte
Pattern Recognition 46 (12), 3490-3506, 2013
Graph cut segmentation with a statistical shape model in cardiac MRI
D Grosgeorge, C Petitjean, JN Dacher, S Ruan
Computer Vision and Image Understanding 117 (9), 1027-1035, 2013
Segthor: Segmentation of thoracic organs at risk in ct images
Z Lambert, C Petitjean, B Dubray, S Kuan
2020 Tenth International Conference on Image Processing Theory, Tools and …, 2020
Segmentation of organs at risk in thoracic CT images using a sharpmask architecture and conditional random fields
R Trullo, C Petitjean, S Ruan, B Dubray, D Nie, D Shen
2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017
Cardiac MRI assessment of right ventricular function in acquired heart disease: factors of variability
J Caudron, J Fares, V Lefebvre, PH Vivier, C Petitjean, JN Dacher
Academic radiology 19 (8), 991-1002, 2012
Automatic cardiac ventricle segmentation in MR images: a validation study
D Grosgeorge, C Petitjean, J Caudron, J Fares, JN Dacher
International journal of computer assisted radiology and surgery 6, 573-581, 2011
Diagnostic accuracy and variability of three semi-quantitative methods for assessing right ventricular systolic function from cardiac MRI in patients with acquired heart disease
J Caudron, J Fares, PH Vivier, V Lefebvre, C Petitjean, JN Dacher
European radiology 21, 2111-2120, 2011
High-level prior-based loss functions for medical image segmentation: A survey
R El Jurdi, C Petitjean, P Honeine, V Cheplygina, F Abdallah
Computer Vision and Image Understanding 210, 103248, 2021
Robust feature selection to predict tumor treatment outcome
H Mi, C Petitjean, B Dubray, P Vera, S Ruan
Artificial intelligence in medicine 64 (3), 195-204, 2015
A non-rigid registration approach for quantifying myocardial contraction in tagged MRI using generalized information measures
N Rougon, C Petitjean, F Prêteux, P Cluzel, P Grenier
Medical Image Analysis 9 (4), 353-375, 2005
Joint segmentation of multiple thoracic organs in CT images with two collaborative deep architectures
R Trullo, C Petitjean, D Nie, D Shen, S Ruan
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
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