Abstract-In the rapidly evolving field of intravascular ultrasound (IVUS), the assessment of vessel morphology still lacks a geometrically correct 3-D reconstruction. The IVUS frames are usually stacked up to form a straight vessel, neglecting curvature and the axial twisting of the catheter during the pullback. Our method combines the information about vessel cross-sections obtained from IVUS with the information about the vessel geometry derived from biplane angiography. First, the catheter path is reconstructed from its biplane projections, resulting in a spatial model. The locations of the IVUS frames are determined and their orientations relative to each other are calculated using a discrete approximation of the Frenet-Serret formulas known from differential geometry. The absolute orientation of the frame set is established utilizing the imaging catheter itself as an artificial landmark. The IVUS images are segmented using our previously developed algorithm. The fusion approach has been extensively validated in computer simulations, phantoms, and cadaveric pig hearts.

Abstract. We present a fast and accurate tool for semiautomatic segmentation of volumetric medical images based on the live wire algorithm, shape-based interpolation and a new optimization method. While the user-steered live wire algorithm represents an efficient, precise and reproducible method for interactive segmentation of selected twodimensional images, the shape-based interpolation allows the automatic approximation of contours on slices between user-defined boundaries. The combination of both methods leads to accurate segmentations with significantly reduced user interaction time. Moreover, the subsequent automated optimization of the interpolated object contours results in a better segmentation quality or can be used to extend the distances between user-segmented images and for a further reduction of interaction time. Experiments were carried out on hepatic computer tomographies from three different clinics. The results of the segmentation of liver parenchyma have shown that the user interaction time can be reduced more than 60% by the combination of shape-based interpolation and our optimization method with volume deviations in the magnitude of inter-user differences.

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The aim of this work is the three-dimensional (3-D) reconstruction of the left or right heart chamber from digital biplane angiograms. The approach used, the binary reconstruction, exploits the density information of subtracted ventriculograms from two orthogonal views in addition to the ventricular contours. The ambiguity of the problem is largely reduced by incorporating a priori knowledge of human ventricles. A model-based reconstruction program is described that is applicable to routinely acquired biplane ventriculographic studies. Prior to reconstruction, several geometric and densitometric imaging errors are corrected. The finding of corresponding density profiles and anatomical landmarks is supported by a biplane image pairing procedure that takes the movement of the gantry system into account. Absolute measurements are based on geometric isocenter calibration and a slice-wise density calibration technique. The reconstructed ventricles allow 3-D visualization and regional wall motion analysis independently of the gantry setting. The method is applied to clinical angiograms and tested in left- and right-ventricular phantoms yielding a well shape conformity even with few model information. The results indicate that volumes of binary reconstructed ventricles are less projection-dependent compared to volume data derived by purely contour-based methods. A limitation is that the heart chamber must not be superimposed by other dye-filled structures in both projections.

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Data fusion of biplane angiography and intravascular ultrasound (IVUS) facilitates geometrically correct reconstruction of coronary vessels. The locations of IVUS frames along the catheter pullback trajectory can be identified, however the IVUS image orientations remain ambiguous. An automated approach to determination of correct IVUS image orientation in three-dimensional space is reported. Analytical calculation of the catheter twist is followed by statistical optimization determining the absolute IVUS image orientation. The fusion method was applied to data acquired in patients undergoing routine coronary intervention, demonstrating the feasibility and good performance of our approach.

The new image-guided stereotactic navigation technique combined with virtual surgery planning can solve the surgeon's dilemma and yield a successful operation.

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