Statistical Atlases and Computational Models of the Heart : Imaging and Modelling Challenges

Open Data:

Intro -- Preface -- Organization -- Contents -- MoCo (Motion Correction) Challenge -- Advanced Normalization Tools for Cardiac Motion Correction -- 1 Introduction -- 2 Materials and Methods -- 2.1 Evaluation Data -- 2.2 Preprocessing and Image Registration -- 3 Evaluation -- 4 Discussion and Conclusions -- References -- Deformable Image Registration and Intensity Correction of Cardiac Perfusion MRI -- 1 Introduction -- 2 Data -- 3 Multi-level Joint Image Registration and Intensity Correction -- 4 Results and Validation -- 5 Discussion and Conclusion -- References -- Comparison of Linear and Non-linear 2D+T Registration Methods for DE-MRI Cardiac Perfusion Studies -- 1 Introduction -- 2 Methods -- 2.1 Image Registration -- 2.2 Motion Compensation Schemes -- 3 Experiments -- 4 Results -- 5 Conclusion -- References -- Motion Correction for Dynamic Contrast-Enhanced CMR Perfusion Images Using a Consecutive Finite Element Model Warping -- 1 Introduction -- 2 Methodology -- 2.1 Initial Rigid Registration -- 2.2 Finite Element Warping -- 3 Regularization -- 3.1 Consecutive Frame Registration -- 3.2 Validation Methods -- 4 Experimental Results -- 5 Discussion -- References -- Deformable and Rigid Model-Based Image Registrationfor Quantitative Cardiac Perfusion -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion and Conclusion -- References -- Automatic Perfusion Analysis Using Phase-Based Registration and Object-Based Image Analysis -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Data -- 2.2 Preprocessing -- 2.3 Motion Correction -- 2.4 Myocardium Segmentation -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- LV Mechanics Challenge -- Left Ventricular Diastolic and Systolic MaterialProperty Estimation from Image Data -- 1 Introduction -- 2 Methods -- 2.1 Geometry Fitting -- 2.2 Fiber Fitting

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