Exploiting spatio-temporal information for view recognition in cardiac echo videos, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.1-8, 2008. ,
DOI : 10.1109/CVPRW.2008.4563008
Random forests-random features, pp.1-29, 1999. ,
Multi-column deep neural networks for image classification, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.3642-3649, 2012. ,
DOI : 10.1109/CVPR.2012.6248110
Decision Forests: A Unified Framework for Classification, Regression , Density Estimation, Manifold Learning and Semi-Supervised Learning. Foundations and Trends in Computer Graphics and Vision, pp.81-227, 2011. ,
Imagenet: A large-scale hierarchical image database, CVPR, 2009. ,
The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart, Bioinformatics, vol.27, issue.16, pp.272288-2295, 2011. ,
DOI : 10.1093/bioinformatics/btr360
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification, 2015 IEEE International Conference on Computer Vision (ICCV), 2015. ,
DOI : 10.1109/ICCV.2015.123
Improving neural networks by preventing co-adaptation of feature detectors:1?18. Available from, 2012. ,
Caffe, Proceedings of the ACM International Conference on Multimedia, MM '14, p.14085093, 2014. ,
DOI : 10.1145/2647868.2654889
Rationale and Design for the Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation (DETERMINE) Trial, Journal of Cardiovascular Electrophysiology, vol.350, issue.9, pp.982-989, 2009. ,
DOI : 10.1111/j.1540-8167.2009.01503.x
Recognizing Image Style:1?20. Available from, 2013. ,
Gradient-based learning applied to document recognition, Proceedings of the IEEE, pp.2278-2324, 1998. ,
DOI : 10.1109/5.726791
Recognizing cardiac magnetic resonance acquisition planes In: Medical Image Understanding and Analysis, 2014. ,
Automatic view recognition for cardiac ultrasound images, International Workshop on Computer Vision for Intravascular and Intracardiac Imaging, pp.187-194, 2006. ,
Automatic Cardiac View Classification of Echocardiogram, 2007 IEEE 11th International Conference on Computer Vision, 2007. ,
DOI : 10.1109/ICCV.2007.4408867
Automatic Cardiac View Classification of Echocardiogram, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007. ,
DOI : 10.1109/ICCV.2007.4408867
Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905
CNN Features Off-the-Shelf: An Astounding Baseline for Recognition, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014. ,
DOI : 10.1109/CVPRW.2014.131
Cardiac MRI view classification using autoencoder, 2014 Cairo International Biomedical Engineering Conference (CIBEC), pp.125-128, 2014. ,
DOI : 10.1109/CIBEC.2014.7020935
Cardiovascular MR Imaging Planes and Segmentation Clinical cardiac mri se -333, Medical Radiology; Available, vol.from, pp.93-107, 2012. ,
Benchmarking framework for myocardial tracking and deformation algorithms: An open access database. Medical image analysis, pp.632-680, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00855928
Automatic view classification for cardiac MRI Barcelona: IEEE, 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.1771-1774, 2012. ,