Treffer 1 - 20 von 34 für Suche 'Sermesant, Maxime', Suchdauer: 0,30s Treffer weiter einschränken
  1. 1
    Eikonal Model Personalisation Using Invasive Data to Predict Cardiac Resynchronisation Therapy Electrophysiological Response
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  2. 2
    Shape Constraints in Deep Learning for Robust 2D Echocardiography Analysis
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  3. 3
    Style Data Augmentation for Robust Segmentation of Multi-modality Cardiac MRI
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  4. 4
    Towards Hyper-Reduction of Cardiac Models Using Poly-affine Transformations
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  5. 5
    Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation
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  6. 6
    Joint Data Imputation and Mechanistic Modelling for Simulating Heart-Brain Interactions in Incomplete Datasets
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  7. 7
    Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection
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  8. 8
    Unsupervised Echocardiography Registration Through Patch-Based MLPs and Transformers
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  9. 9
    Functional imaging and modeling of the heart : 5th international conference, FIMH 2009 Nice, France, June 3-5, 2009 ; proceedings
    Veröffentlicht 2009
    Inhaltsverzeichnis
    Cover
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  10. 10
    Non-invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-Driven or Model-Based?
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  11. 11
    Personal-by-Design: A 3D Electromechanical Model of the Heart Tailored for Personalisation
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  12. 12
    APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics
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  13. 13
    EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology
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  14. 14
    Automatic Multiplanar CT Reformatting from Trans-Axial into Left Ventricle Short-Axis View
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  15. 15
    Scar-Related Ventricular Arrhythmia Prediction from Imaging Using Explainable Deep Learning
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  16. 16
    End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Quality
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  17. 17
    Phase-Independent Latent Representation for Cardiac Shape Analysis
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  18. 18
    Estimation of Imaging Biomarker’s Progression in Post-infarct Patients Using Cross-sectional Data
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  19. 19
    Interpretable Prediction of Post-Infarct Ventricular Arrhythmia Using Graph Convolutional Network
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  20. 20
    Statistical atlases and computational models of the heart : imaging and modelling challenges ; 5th international workshop, STACOM 2014, held in conjunction with MICCAI 2014, Boston, MA, USA, September 18, 2014 ; revised selected papers
    Veröffentlicht 2015
    Inhaltsverzeichnis
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