Thomas Schiwietz

A fast and high-quality cone beam reconstruction pipeline using the GPU

Cone beam scanners have evolved rapidly in the past years. Increasing sampling resolution of the projection images and the desire to reconstruct high resolution output volumes increases both the memory consumption and the processing time considerably. In order to keep the processing time down new strategies for memory management are required as well as new algorithmic implementations of the reconstruction pipeline. In this paper, we present a fast and high-quality cone beam reconstruction pipeline using the Graphics Processing Unit (GPU). This pipeline includes the backprojection process and also pre-filtering and post-filtering stages. In particular, we focus on a subset of five stages, but more stages can be integrated easily. In the pre-filtering stage, we first reduce the amount of noise in the acquired projection images by a non-linear curvature-based smoothing algorithm. Then, we apply a high-pass filter as required by the inverse Radon transform. Next, the backprojection pass reconstructs a raw 3D volume. In post-processing, we first filter the volume by a ring artifact removal. Then, we remove cupping artifacts by our novel uniformity correction algorithm. We present the algorithm in detail. In order to execute the pipeline as quickly as possible we take advantage of GPUs that have proven to be very fast parallel processors for numerical problems. Unfortunately, both the projection images and the reconstruction volume are too large to fit into 512 MB of GPU memory. Therefore, we present an efficient memory management strategy that minimizes the bus transfer between main memory and GPU memory. Our results show a 4 times performance gain over a highly optimized CPU implementation using SSE2/3 commands. At the same time, the image quality is comparable to the CPU results with an average per pixel difference of 10-5.

Numerical Simulations on PC Graphics Hardware

On recent PC graphics cards, fully programmable parallel geometry and pixel units are available providing powerful instruction sets to perform arithmetic and logical operations. In addition to computational functionality, pixel (fragment) units also provide an efficient memory interface to local graphics data.

Freeform Image

A technology for automatically creating and adding the sound to interactive CG animations of spark discharges in real time has been developed. In the procedure proposed in this paper, the user inputs the electric charge distribution, boundary conditions and other parameters affecting the initiation of electric discharges in virtual space. The animation of the discharge is then created by generating the shape of the discharge pattern and rendering it, and the sound synchronized with the animation is automatically generated in real time. The noises from spark discharges are shock waves, which exhibit complicated behavior; but, in this study, an empirical shape for a shock wave is employed to efficiently generate the acoustic waveform. Effective procedures for expressing lightning discharges and continuous discharges are also proposed.In this paper we present a technique for image deformation in which the user is given flexible control over what kind of deformation to perform. Freeform image extends available image deformation techniques in that it provides a palette of intuitive tools including interactive object segmentation, stiffness editing and force-based controls to achieve both a natural look and realistic animations of deforming parts. The model underlying our approach is physics-based and it is amenable to a variety of different kinds of image manipulations ranging from as-rigid- as-possible to fully elastic deformations. We have developed a multigrid solver for quadrangular finite elements, which achieves real-time performance for high resolution pixel grids. On recent CPUs this solver can handle about 16K co-rotated finite elements at roughly 60 ms.