Guido P. M. Prause

Binary reconstruction of the heart chambers from biplane angiographic image sequences

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.

Local-cost computation for efficient segmentation of 3D objects with live wire

We present an approach for the optimization of the live wire algorithm applied to 3D medical images. Our method restricts the computation of the cost function to relevant areas and considers regionally specific properties of the object boundary. As a consequence, precise contours can be obtained in reduced computation and interaction time. For the calculation of the cost function on the current image slice, the nearest contour on an adjacent slice is taken as reference. The reference contour is divided into local segments and the image pixels are classified into regions with respect to their distance to the contour segments. The size of these regions is controlled by a given maximum distance. Cost function parameters are learned separately from every local contour segment of the reference slice and define the cost function for the respective region on the current slice. We used the local cost computation for the interactive definition of object contours, as well as for the optimization of interpolated contours between user-defined contours. Applied to CT and MR data of the liver, our method showed considerable advantages over the conventional algorithm based on a global cost function, particularly for objects with inhomogeneities or with different surrounding tissue.

Geometric image correction and iso-center calibration at oblique biplane angiographic views

In the X-ray image intensifier TV system there are geometric image distortions which can be subdivided into pincushion distortions, S-shaped warping, image twisting, and shifting. These errors depend partly on the direction of the geomagnetic field relative to the image intensifier axis and are to be corrected for each view specifically. For caudal or cranial views there is the additional problem that in biplane images the slices of an object are projected on oblique lines. Based on four small bronze washers marking a centered square on each image intensifier screen, a dewarping program automatically calculates a nonlinear polynomial transformation. Then, all points of the image or the study are dewarped and centered accordingly. At the same time, the geometric calibration factors are derived. From the registered viewing angles, those angles are calculated by which both images have to be rotated for biplane assignment. Both optimal biplane visualization and the basis for further analyses are achieved.<<ETX>>

3D catheter path reconstruction from biplane angiograms

The 3D coronary vessels can be reconstructed by means of different cardiac imaging modalities. Two of the most widely used modalities for the purpose of coronary tree reconstruction are intravascular ultrasounds (IVUS) and biplane angiography. Current 3D vessel reconstruction based on IVUS pullback imaging is limited by the lack of information about the real vessel curvature, because the path of the catheter is assumed to be a straight line. This limitation can be overcome if information from an IVUS sequence is fused with a biplane X-ray image of the catheter acquired at the start of the pullback procedure. This work focuses on the reconstruction of the catheter path from biplane angiograms. This reconstruction represents the 3D path followed by the catheter inside the vessel of interest. While other approaches reconstruct the vessel after it has been segmented in both images independently, our approach, based on the snakes technique, allows us to segment and reconstruct the catheter trajectory merging information from both images simultaneously. The result is a more robust reconstruction since 3D constraints can be used and no correspondence of points between the projections is required. This reconstruction will allow a posterior more exact combination of IVUS and biplane angiography image modalities.

Automated calculation of the axial orientation of intravascular ultrasound images by fusion with biplane angiography

This paper presents an approach for fusion of the two major cardiovascular imaging modalities, angiography and intravascular ultrasound (IVUS). While the path of the IVUS catheter, which follows the vessel curvature during pullback, is reconstructed from biplane angiograms, cross-sectional information about the vessel is derived from IVUS. However, after mapping of the IVUS frames into their correct 3-D locations along the catheter path, their orientations remain ambiguous. We determine the relative catheter twisting analytically, followed by a statistical method for finding the absolute orientation from the out-of-center position of the IVUS catheter. Our results as obtained from studies with cadaveric pig hearts and from three patients undergoing routine coronary intervention showed a good match of the absolute orientation by the algorithm. In all tested cases, the method determined the visually correct orientations of the IVUS frames. Local distortions were reliably identified and discarded.

Objective methods for optimizing JPEG compression of coronary angiographic images.

Digital angiographic images contain a significant amount of redundancy as well as some irrelevant information and noise. Therefore, it is possible to reduce the number of bits required to represent an image considerably. The lossy JPEG standard may be used provided that no significant diagnostic information is lost. As implemented in presently available hard- and software in most cases the luminance quantization table (LQT) is applied for gray level images, which may only be scaled by a so-called quality factor. The questions arise whether it is possible and worthwhile to specify quantization tables for the particular characteristics of angiograms.To assess the quality performance quantitatively, global numerical quality measures and evaluations based on Hosaka-plots were performed. Those diagrams compare the errors introduced into areas of different local activity. By the newly introduced weighting of these errors with the relative occupancy of the respective classes of activity the results got more reproducible. The blocking and blurring effects introduced by lossy JPEG compression could be compared objectively.Two new quantization tables were derived from the transfer function of the angiographic X-ray system, the modulation transfer quantization table (MTQT) and the star pattern quantization table (SPQT). Both tables guarantee that the blurring of sharp edges is minimized so that no deterioration around a coronary lesion occurs. Based on the signal-to-noise ratio, the overall quality performance is the same as for theLQT. A general relation between the bit rate of the compressed image and the quality factor has been determined for images of high local activity and normally scaled coronary angiographic images (512 × 512).

Heart Chamber Reconstruction from Biplane Angiography

In this chapter we describe an application of the binary tomography technique to routinely acquired biplane cardiac angiograms. The described model-based reconstruction approach aims to recover the 3D shape of the left or right heart chamber from the density profiles of orthogonal biplane ventriculograms. Several geometric and densitometric imaging errors need to be corrected in the clinical data before the moving heart chamber may be reconstructed slice-by-slice and frame-by-frame. The ventricular reconstructions allow for 3D visualization, volume determination, and regional wall motion analysis independently of the gantry setting used for image acquisition. The method has been 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.

Steps of image correction and processing for the binary reconstruction of the ventricles from biplane angiocardiograms

The binary reconstruction of the ventricles from clinically acquired biplane angiocardiograms requires the preprocessing of the raw image data. The necessary steps of densitometric and geometric image correction and processing are presented and discussed. By means of an end-diastolic laevocardiogram their effects are demonstrated by comparing the biplane row sum vectors. The corrected projection data are used for the binary reconstruction of the ventricle.<<ETX>>

Planning of anatomical resections and in situ ablations in oncologic liver surgery

Abstract We describe a software system that helps both to determine anatomically correct and surgically realizable resection territories and to plan minimally invasive interventions for cases that are impracticable for surgery.

Quantization table design for JPEG compression of angiocardiographic images

The lossy JPEG standard may be used for high performance image compression. As implemented in presently available hard- and software in most cases the so-called luminance quantization table is applied for gray level images, which may be scaled by a quality factor. The questions arise which quality factor is optimal and whether it is possible and worthwhile to specify quantization tables for the particular characteristics of angiocardiograms. Two new quantization tables are derived from the transfer function of the angiocardiographic system, which is a worst-case approach with respect to preserving sharp edges. To assess the performance, evaluations based on Hosaka-plots are developed. These diagrams compare the different errors introduced by lossy JPEG compression objectively.<<ETX>>