Automatic trinocular 3D reconstruction of coronary artery centerlines from rotational X-ray angiography

Abstract

We present a method for fully automatic 3D reconstruction of coronary artery centerlines using three X-ray angiogram projections from a single rotating monoplane acquisition. The reconstruction method consists of three steps: (1) filtering and segmenting the images using a multiscale analysis, (2) matching points in two of the segmented images using the information from the third image, and (3) reconstructing in 3D the matched points. This method needs good calibration of the system geometry and requires breatheld acquisitions. The final algorithm is formulated as an energy minimization problem that we solve using dynamic programming optimization. This method provides a fast and automatic way to compute 3D models of vessels centerlines. It has been applied to both phantoms, for validation purposes, and patient data sets.

Reconstruction of coronary arteries from a single rotational X-ray projection sequence

“…The rotational acquisition allows to get between 3 and 7 reference frames, depending on gantry rotation speed and on patient heart rate. We propose to use all the available images to perform a multi-ocular matching of the extracted centerlines in reference images, as basically described in [22]. This is achieved by optimizing a matching criterion detailed below.…”

4-D Tomographic Representation of Coronary Arteries from One Rotational X-Ray Sequence

“…All the possibly matching points are reconstructed in 3-D and projected in the remaining reference frames. To disambiguate the matching, we compute a "point score" as the sum of the multiscale responses of these projected points [1]. The point score is combined with a geometrical regularizing term in a dynamic programming method to reconstruct 3-D curves from the set of 2-D curves in reference frame i 1 .…”

“…To disambiguate the matching, we compute a "point score" as the sum of the multiscale responses of these projected points [1]. The point score is combined with a geometrical regularizing term in a dynamic programming method to reconstruct 3-D curves from the set of 2-D curves in reference frame i 1 . By taking all possible ordered pairs of reference frames (i k , i l ) we obtain several, partially redundant, 3-D centerlines models.…”

Fully automatic 3D segmentation of coronary arteries based on mathematical morphology

“…3D reconstruction (i.e. segmentation and 3D surfacic visualisation) of the coronary arteries from angiograms would lead to higher accuracy and reproducibility in the diagnosis and to better precision in the quantification of the severity of the diseases [2].…”