Epicardial surface estimation from coronary angiograms
Computer Vision, Graphics, and Image Processing
The NURBS book
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Landmark-Based Image Analysis: Using Geometric and Intensity Models
Approximate Thin Plate Spline Mappings
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Applied Numerical Mathematics - Special issue: Applied numerical computing: Grid generation and solution methods for advanced simulations
Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis
Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis
Visualization and Processing of Tensor Fields: Advances and Perspectives
Visualization and Processing of Tensor Fields: Advances and Perspectives
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Pathological processes cause abnormal regional motions of the heart. Regional wall motion analyses are important to evaluate the success of therapy, especially of cell therapy, since the recovery of the heart in cell therapy proceeds slowly and results in only small changes of ventricular wall motility. The usual ultrasound imaging of heart motion is too inaccurate to be considered as an appropriate method. MRI studies are more accurate, but insufficient to reliably detect small changes in regional ventricular wall motility. We thus aim at a more accurate method of motion analysis. Our approach is based on two imaging modalities, viz. cardiac CT and biplane cineangiography. The epicardial surface represented in the CT data set at the end of the diastole is registered to the three-dimensionally reconstructed epicardial artery tree from the angiograms in end-diastolic position. The motion tracking procedures are carried out by applying thin-plate spline transformations between the epicardial artery trees belonging to consecutive frames of our cineangiographic imagery.