An approach to the three-dimensional reconstruction of coronary arteries is presented. The principal objective is to show how modeling of a vascular network, together with algorithmic procedures, can lead to accurate 3-D structure and feature labeling. The labeling problem is stated directly within the 3-D reconstruction framework. The reconstruction ambiguities inherent to biplane techniques are solved by means of a knowledge base, modeling of the object, and heuristic rules. Feasibility in near-real situations has been demonstrated. The critical importance of the object 3-D reference to achieving the data and modeling matching is emphasized, and a way to deal with it is pointed out. The overall system implies an incremental development in methodologies and experiments. All of them have been elaborated and tested independently, and the most appropriate ones have been selected for integration into a modular system. All the stages of the process (calibration, segmentation, reconstruction, and display) are discussed, with the main focus on modeling. Examples of automatic reconstruction from a phantom are provided.

We address the problem of reconstructing a three-dimensional volume from a set of two-dimensional X-ray projections. We present a time efficient solution based on a multiscale estimation technique. Estimation is first performed at a coarse resolution. Then the resolution is increased step by step and at each step a new estimation is performed, using an initial value derived from the volume estimated at the preceding level of resolution. The method is illustrated by results obtained on geometric and anatomic phantoms.

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