Karel J. Zuiderveld

Acceleration of ray-casting using 3-D distance transforms

This paper introduces a novel approach for speeding up the ray casting process commonly used in volume visualization methods. This new method called Ray Acceleration by Distance Coding (RADC) uses a 3-D distance transform to determine the minimum distance to the nearest interesting object; the implementation of a fast and accurate distance transform is described in detail. High distance values, typically found at off-center parts of the volume, cause many sample points to be skipped, thus significantly reducing the number of samples to be evaluated during the ray casting step. The minimum distance values that are encountered while traversing the volume can be used for the identification of rays that do not hit objects. Our experiments indicate that the RADC method can reduce the number of sample points by a factor between 5 and 20.

Image reconstruction by convolution with symmetrical piecewise nth-order polynomial kernels

The reconstruction of images is an important operation in many applications. From sampling theory, it is well known that the sine-function is the ideal interpolation kernel which, however, cannot be used in practice. In order to be able to obtain an acceptable reconstruction, both in terms of computational speed and mathematical precision, it is required to design a kernel that is of finite extent and resembles the sinc-function as much as possible. In this paper, the applicability of the sine-approximating symmetrical piecewise nth-order polynomial kernels is investigated in satisfying these requirements. After the presentation of the general concept, kernels of first, third, fifth and seventh order are derived. An objective, quantitative evaluation of the reconstruction capabilities of these kernels is obtained by analyzing the spatial and spectral behavior using different measures, and by using them to translate, rotate, and magnify a number of real-life test images. From the experiments, it is concluded that while the improvement of cubic convolution over linear interpolation is significant, the use of higher order polynomials only yields marginal improvement.

Image Registration for Digital Subtraction Angiography

In clinical practice, Digital Subtraction Angiography (DSA) is a powerful technique for the visualization of blood vessels in the human body. The diagnostic relevance of the images is often reduced by artifacts which arise from the misalignment of successive images in the sequence, due to patient motion. In order to improve the quality of the subtraction images, several registration techniques have been proposed. However, because of the required computation times, it has never led to algorithms that are fast enough so as to be acceptable for integration in clinical applications. In this paper, a new approach to the registration of digital angiographic images is proposed. It involves an edge-based selection of control points for which the displacement is computed by means of template matching, and from which the complete displacement vector field is constructed by means of interpolation. The final warping of the images according to the calculated displacement vector field is performed real-time by graphics hardware. Experimental results with several clinical data sets show that the proposed algorithm is both effective and very fast.

Parallel implementations of AOS schemes: a fast way of nonlinear diffusion filtering

In most cases nonlinear diffusion filtering is implemented by means of explicit finite difference schemes. These algorithms are not very efficient, since they are only stable for small time steps. We address this problem by presenting unconditionally stable semi-implicit schemes which are based on an additive operator splitting (AOS). They are very efficient since they can be implemented by recursive filtering, and their separability allows a straightforward implementation in any dimension. We analyse their behaviour on a parallel computer and demonstrate that parallel AOS schemes on a modern shared-memory multiprocessor system with 8 processors allow a speed-up of two orders of magnitude in comparison to the widely-used explicit scheme on a single processor.

Image guidance of endovascular interventions on a clinical MR scanner

Magnetic resonance imaging (MRI) offers potential advantages over conventional X-ray techniques for guiding and evaluating vascular interventions. Image guidance of such interventions via passive catheter tracking requires real-time image processing. Commercially available MR scanners currently do not provide this functionality. This paper describes an image processing environment that allows near-real-time MR-guided vascular interventions. It demonstrates (1) that flexibility can be achieved by separating the scanner and the image processing/display system, thereby preserving the stability of the scanner and (2) that sufficiently rapid visualization can be achieved by low-cost workstations equipped with graphics hardware. The setup of the hardware and the software is described in detail. Furthermore, image processing techniques are presented for guiding the interventionalist through simple vascular anatomy. Finally, results of a phantom balloon angioplasty experiment are presented.

Multi-modal volume visualization using object-oriented methods

This article describes an object-oriented software architecture aimed at integrated visualization of volumetric a’atasetsfrom d@erent modalities. The design supports the implementation of objectspeci

Techniques for speeding up high-quality perspective maximum intensity projection

c visualization algorithms and allows for true integrated 30 visualization using arbitrary combinations of rendering techniques such as sutiace rendering, volume rendering and shape-based interpolation. The feasibility of the proposed approach is illustrated by means of three applications. Some important lessons to be learned from naiLely applying object-oriented methodology to volume visualization are discussed. The current status of the research is described and possible extensions are outlined.

Multimodality visualization of medical volume data

Abstract This paper presents three classes of speed-up techniques for calculating high-quality perspective Maximum Intensity Projection (MIP) images from Magnetic Resonance Angiography (MRA) data. The method of choice is a combination of Ray Acceleration by Distance Coding (RADC) with Closest Vessel Projection (CVP); this technique combines a five- to ten-fold speed improvement with improved visualization of blood vessels.

Automated lumen definition from 30 MHz intravascular ultrasound images

Abstract New developments in 3-D volume acquisitions are creating a rapidly increasing demand for integrating multimodality 3-D visualization. In order to accomplish routine clinical multimodality visualization, many issues have to be dealt with, such as techniques for accurate spatial registration, integrated representation, suitable graphical user interfaces, and obtaining adequate rendering speeds. The aim of this experience paper is 2-fold. First, it presents various results from our research on multimodality visualization/registration. Second, this paper explicitly addresses practical problems and findings related to software development and multimodality registration/visualization. We hope that this will give colleagues a better understanding in some of these issues based on our experience, including notably our mistakes.

Fast Noise Reduction in Computed Tomography for Improved 3-D Visualization

One prerequisite for standard clinical use of intravascular ultrasound imaging is rapid evaluation of the data. The main quantities to be extracted from the data are the size and the shape of the lumen. Until now, no accurate, robust and reproducible method to obtain the lumen boundaries from intravascular ultrasound images has been described. In this study, 21 different (semi-)automated binary-segmentation methods for determining the lumen are compared with manual segmentation to find an alternative for the laborious and subjective procedure of manual editing. After a preprocessing step in which the catheter area is filled with lumen-like grey values, all approaches consist of two steps: (i) smoothing the images with different filtering methods and (ii) extracting the lumen by an object definition method. The combination of different filtering methods and object definition methods results in a total of 21 methods and 80 experiments. The results are compared with a reference image, obtained from manual editing, by use of four different quality parameters--two based on squared distances and two based on Mahalanobis distances. The evaluation has been carried out on 15 images, of which seven are obtained before balloon dilation and eight after balloon dilation. While for the post-dilation images no definite conclusions can be drawn, an automated contour model applied to images smoothed with a large kernel appears to be a good alternative to manual contouring. For pre-dilation images a fully automated active contour model, initialized by thresholding, preceded by filtering with a small-scale median filter is the best alternative for manual delineation. The results of this method are even better than manual segmentation, i.e. they are consistently closer to the reference image than the average distance of all individual manual segmentations.