Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware.

Algebraic reconstruction methods, such as the algebraic reconstruction technique (ART) and the related simultaneous ART (SART). reconstruct a two-dimensional (2-D) or three-dimensional (3-D) object from its X-ray projections. The algebraic methods have, in certain scenarios, many advantages over the more popular Filtered Backprojection approaches and have also recently been shown to perform well for 3-D cone-beam reconstruction. However, so far the slow speed of these iterative methods have prohibited their routine use in clinical applications. In this paper, we address this shortcoming and investigate the utility of widely available 2-D texture mapping graphics hardware for the purpose of accelerating the 3-D algebraic reconstruction. We find that this hardware allows 3-D cone-beam reconstructions to be obtained at almost interactive speeds, with speed-ups of over 50 with respect to implementations that only use general-purpose CPUs. However, we also find that the reconstruction quality is rather sensitive to the resolution of the framebuffer, and to address this critical issue we propose a scheme that extends the precision of a given framebuffer by 4 bits, using the color channels. With this extension, a 12-bit framebuffer delivers useful reconstructions for 0.5% tissue contrast, while an 8-bit framebuffer requires 4%. Since graphics hardware generates an entire image for each volume projection, it is most appropriately used with an algebraic reconstruction method that performs volume correction at that granularity as well, such as SART or SIRT. We chose SART for its faster convergence properties.

Anti-aliased three-dimensional cone-beam reconstruction of low-contrast objects with algebraic methods.

This paper examines the use of the algebraic reconstruction technique (ART) and related techniques to reconstruct 3-D objects from a relatively sparse set of cone-beam projections. Although ART has been widely used for cone-beam reconstruction of high-contrast objects, e.g., in computed angiography, the work presented here explores the more challenging low-contrast case which represents a little-investigated scenario for ART. Preliminary experiments indicate that for cone angles greater than 20 degrees, traditional ART produces reconstructions with strong aliasing artifacts. These artifacts are in addition to the usual off-midplane inaccuracies of cone-beam tomography with planar orbits. We find that the source of these artifacts is the nonuniform reconstruction grid sampling and correction by the cone-beam rays during the ART projection-backprojection procedure. A new method to compute the weights of the reconstruction matrix is devised, which replaces the usual constant-size interpolation filter by one whose size and amplitude is dependent on the source-voxel distance. This enables the generation of reconstructions free of cone-beam aliasing artifacts, at only little extra cost. An alternative analysis reveals that simultaneous ART (SART) also produces reconstructions without aliasing artifacts, however, at greater computational cost. Finally, we thoroughly investigate the influence of various ART parameters, such as volume initialization, relaxation coefficient lambda, correction scheme, number of iterations, and noise in the projection data on reconstruction quality. We find that ART typically requires only three iterations to render satisfactory reconstruction results.

Fast implementations of algebraic methods for three-dimensional reconstruction from cone-beam data.

The prime motivation of this work is to devise techniques that make the algebraic reconstruction technique (ART) and related methods more efficient for routine clinical use, while not compromising their accuracy. Since most of the computational effort of ART is spent for projection/backprojection operations, we first seek to optimize the projection algorithm. Existing projection algorithms are surveyed and it is found that these algorithms either lack accuracy or speed, or are not suitable for cone-beam reconstruction. We hence devise a new and more accurate extension to the splatting algorithm, a well-known voxel-driven projection method. We also describe a new three-dimensional (3-D) ray-driven projector that is considerably faster than the voxel-driven projector and, at the same time, more accurate and perfectly suited for the demands of cone beam. We then devise caching schemes for both ART and simultaneous ART (SART), which minimize the number of redundant computations for projection and backprojection and, at the same time, are very memory conscious. We find that with caching, the cost for an ART projection/backprojection operation can be reduced to the equivalent cost of 1.12 projections. We also find that SART, due to its image-based volume correction scheme, is considerably harder to accelerate with caching. Implementations of the algorithms yield run-time ratios TSART/TART between 1.5 and 1.15, depending on the amount of caching used.

Segmentation of medical images using LEGION.

Advances in visualization technology and specialized graphic workstations allow clinicians to virtually interact with anatomical structures contained within sampled medical-image datasets. A hindrance to the effective use of this technology is the difficult problem of image segmentation. In this paper, we utilize a recently proposed oscillator network called the locally excitatory globally inhibitory oscillator network (LEGION) whose ability to achieve fast synchrony with local excitation and desynchrony with global inhibition makes it an effective computational framework for grouping similar features and segregating dissimilar ones in an image. We extract an algorithm from LEGION dynamics and propose an adaptive scheme for grouping. We show results of the algorithm to two-dimensional (2-D) and three-dimensional (3-D) (volume) computerized topography (CT) and magnetic resonance imaging (MRI) medical-image datasets. In addition, we compare our algorithm with other algorithms for medical-image segmentation, as well as with manual segmentation. LEGION's computational and architectural properties make it a promising approach for real-time medical-image segmentation.

Functional endoscopic sinus surgery training simulator.

OBJECTIVE/HYPOTHESIS: To determine the efficacy of a haptic (force feedback) device and to compare isosurface and volumetric models of a functional endoscopic sinus surgery (FESS) training simulator. STUDY DESIGN: A pilot study involving faculty and residents from the Department of Otolaryngology at The Ohio State University. METHODS: Objective trials evaluated the haptic device's ability to perceive three-dimensional shapes (stereognosis) without the aid of image visualization. Ethmoidectomy tasks were performed with both isosurface and volumetric FESS simulators, and surveys compared the two models. RESULTS: The haptic device was 77% effective for stereognosis tasks. There was a preference toward the isosurface model over the volumetric model in terms of visual representation, comfort, haptic-visual fidelity, and overall performance. CONCLUSIONS: The FESS simulator uses both visual and haptic feedback to create a virtual reality environment to teach paranasal sinus anatomy and basic endoscopic sinus surgery techniques to ear, nose, and throat residents. The results of the current study showed that the haptic device was accurate in and of itself, within its current physical limitations, and that the isosurface-based simulator was preferred.

Using advanced simulation technology for cranial base tumor evaluation.

Skull base tumors are considered one of the most difficult pathologic entities to diagnose and treat. The physician is heavily dependent on imaging studies to determine the best form of treatment. As imaging technology becomes more advanced, the physician will need to be able to intuitively explore the complex data. Such intuitive exploration requires the use of high performance computer hardware and software. Issues related to this concept and a summary of current work in this area are presented.

A comparative analysis of integrating visual representations with haptic displays.

As further advances in visual display technologies and force feedback devices are integrated in virtual systems, questions remain: What level of reality does the system provide to the user? Is the environment convincing enough to engage the user and to maximize transfer? Are the visual and haptic displays fully integrated to provide seamless operation in the simulated environment? Does the system provide not only the ability to navigate through a simulated environment, but also realistic interaction with instrumentation and structures? We report on our advances in developing a virtual simulation system for training in functional endoscopic sinus surgery (FESS). Specifically, we will present work on subject trials exploring the realism provided by integrated visual and haptic displays, and compare and contrast surface vs. volume representation for presenting realistic models of the anatomy for surgical interaction.

The weighted-distance scheme: a globally optimizing projection ordering method for ART.

The order in which the projections are applied in the algebraic reconstruction technique (ART) has a great effect on speed of convergence, accuracy, and the amount of noise-like artifacts in the reconstructed image. In this paper, a new projection ordering scheme for ART is presented: the weighted-distance scheme (WDS). It heuristically optimizes the angular distance of a newly selected projection with respect to an extended sequence of previously applied projections. This sequence of influential projections may incorporate the complete set of all previously applied projections or any limited time interval subset thereof. The selection algorithm results in uniform sampling of the projection access space, minimizing correlation in the projection sequence. This produces more accurate images with less noise-like artifacts than previously suggested projection ordering schemes.

Visualization of compression neuropathies through volume deformation.

This paper describes an interdisciplinary effort to simulate and visualize the mechanisms involved in compression neuropathies, specifically tissue deformation occurring during vaginal delivery. These neuropathies often evolve into chronic pelvic pain. We present our methodologies of using high resolution magnetic resonance acquisitions from submillimeter pulse sequences to develop interactive computer simulations based on physically plausible volume models to drive 3D simulations of childbirth. This effort will elucidate tissue movements and mechanics involved in pain disorders and better explain the etiology of these disorders.

A volumetric approach to virtual simulation of functional endoscopic sinus surgery.

Advanced display technologies have made the virtual exploration of relatively complex models feasible in many applications. Unfortunately, only a few human interfaces allow natural interaction with the environment. Moreover, in surgical applications, such realistic interaction requires real-time rendering of volumetric data-placing an overwhelming performance burden on the system. We report on a collaboration of an interdisciplinary group developing a virtual reality system that provides intuitive interaction with volume data by employing real-time volume rendering and force feedback (haptic) sensations. We describe our rendering methods and the haptic devices and explain its utility of this system in the real-world application of Endoscopic Sinus Surgery (ESS) simulation.

ENT endoscopic surgical training simulator.

This paper describes work in progress on the design and development of a prototype simulator for minimally invasive otolaryngology surgical training. The anatomy of the paranasal sinuses is geometrically complex and dangerously close to the brain and orbits, making this procedure challenging to practice and difficult to learn. We discuss the potential role of computer simulation to enhance and accelerate acquisition of surgical skills. The design goals of the prototype include high-fidelity simulation of the endoscopic imagery and haptic cues of surgical palpation. The prototype enables endoscopic navigation and limited interactive tissue manipulation and dissection tasks on a virtual patient using realistic replicas of surgical tools. We present an overview of the system architecture with a discussion of the technological challenges, design issues and current status of the efforts.

Cranial base tumor visualization through high-performance computing.

Tumors of the skull base in general are considered among the more difficult head and neck pathological entities to treat surgically; some surgeons, in fact, consider lesions in this area inoperable. The most appropriate and safest surgical approach to lesions of the anterior and lateral skull base can be devised only with accurate and precise pre-operative assessment. The literature demonstrates the constant evolution of and search for more efficient less invasive, and safe surgical approaches to this region. With the development of a more exact three-dimensional, interactive anatomical "road map" for each patient's disease and anatomy, the skull base surgeon can not only achieve a more accurate pre-operative assessment leading to a less invasive and less morbid approach, but also can continue to develop and refine new approaches without fear of actual morbidity and mortality. An interdisciplinary team approach, the advent and continued development of faster high performance computers, and the development of new and innovative rendering algorithms can lead to surgical simulation. A prototype of an interactive system has been developed. The system will be iteratively modified through a stepwise evaluation of its clinical usefulness by continually reassessing the system with clinical trials. The current state of the system and the potential benefits are presented.

A survey of architectures for volume rendering.

Five hardware architectures for volume rendering, which requires efficiently handling a huge amount of volumetric data, are surveyed, categorized, and compared. They are Cube, Insight, PARCUM, Voxel Processor, and 3DP. General-purpose graphics systems that exploit their surface-based geometry engine to reduce the computational burden of the rendering process are briefly reviewed.