Abstract
This paper presents a model-based reconstruction method of the coronary tree from a few number of projections in rotational angiography imaging. The reconstruction relies on projections acquired at a same cardiac phase and an energy function minimization that aims to lead the deformation of the 3D model to fit projection data whereas preserving coherence both in time and space. Some preliminary results are provided on simulated rotational angiograms.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms
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Artificial Intelligence
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Computer Simulation
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Coronary Angiography / methods*
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Coronary Artery Disease / diagnostic imaging*
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Humans
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Imaging, Three-Dimensional / methods*
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Models, Biological*
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Pattern Recognition, Automated / methods*
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Radiographic Image Enhancement / methods
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Radiographic Image Interpretation, Computer-Assisted / methods*
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Reproducibility of Results
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Rotation
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Sensitivity and Specificity
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Tomography, X-Ray Computed / methods*