Bruno De Man

Distance-driven projection and backprojection in three dimensions

Projection and backprojection are operations that arise frequently in tomographic imaging. Recently, we proposed a new method for projection and backprojection, which we call distance-driven, and that offers low arithmetic cost and a highly sequential memory access pattern. Furthermore, distance-driven projection and backprojection avoid several artefact-inducing approximations characteristic of some other methods. We have previously demonstrated the application of this method to parallel and fan beam geometries. In this paper, we extend the distance-driven framework to three dimensions and demonstrate its application to cone beam reconstruction. We also present experimental results to demonstrate the computational performance, the artefact characteristics and the noise-resolution characteristics of the distance-driven method in three dimensions.

An outlook on x-ray CT research and development

Over the past decade, computed tomography (CT) theory, techniques and applications have undergone a rapid development. Since CT is so practical and useful, undoubtedly CT technology will continue advancing biomedical and non-biomedical applications. In this outlook article, we share our opinions on the research and development in this field, emphasizing 12 topics we expect to be critical in the next decade: analytic reconstruction, iterative reconstruction, local/interior reconstruction, flat-panel based CT, dual-source CT, multi-source CT, novel scanning modes, energy-sensitive CT, nano-CT, artifact reduction, modality fusion, and phase-contrast CT. We also sketch several representative biomedical applications.

Modelling the physics in the iterative reconstruction for transmission computed tomography

There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of x-ray CT imaging. IR has the ability to significantly reduce patient dose; it provides the flexibility to reconstruct images from arbitrary x-ray system geometries and allows one to include detailed models of photon transport and detection physics to accurately correct for a wide variety of image degrading effects. This paper reviews discretization issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. The widespread implementation of IR with a highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modelling.

CatSim: a new computer assisted tomography simulation environment

We present a new simulation environment for X-ray computed tomography, called CatSim. CatSim provides a research platform for GE researchers and collaborators to explore new reconstruction algorithms, CT architectures, and X-ray source or detector technologies. The main requirements for this simulator are accurate physics modeling, low computation times, and geometrical flexibility. CatSim allows simulating complex analytic phantoms, such as the FORBILD phantoms, including boxes, ellipsoids, elliptical cylinders, cones, and cut planes. CatSim incorporates polychromaticity, realistic quantum and electronic noise models, finite focal spot size and shape, finite detector cell size, detector cross-talk, detector lag or afterglow, bowtie filtration, finite detector efficiency, non-linear partial volume, scatter (variance-reduced Monte Carlo), and absorbed dose. We present an overview of CatSim along with a number of validation experiments.

The calculation of the transient near and far field of a baffled piston using low sampling frequencies

A method is presented to calculate the near- and far-field transient radiation of acoustical transducers using low sampling frequencies. The method is based on the classical impulse response approach and on the fact that in practical use the spectrum of the excitation function of a transducer is band limited. This makes it possible to use a smoothed version of the impulse response function. A simple expression to calculate this smoothed function, for a rectangular or circular transducer, is derived. The proposed solution allows accurate computation of pressure fields and backscatter signals, while avoiding high sampling frequencies in the far field of the transducers. Several examples illustrate the accuracy of this new solution and its use for spectral analysis of simulated reflected signals.

Multi-source inverse geometry CT: a new system concept for x-ray computed tomography

Third-generation CT architectures are approaching fundamental limits. Spatial resolution is limited by the focal spot size and the detector cell size. Temporal resolution is limited by mechanical constraints on gantry rotation speed, and alternative geometries such as electron-beam CT and two-tube-two-detector CT come with severe tradeoffs in terms of image quality, dose-efficiency and complexity. Image noise is fundamentally linked to patient dose, and dose-efficiency is limited by finite detector efficiency and by limited spatio-temporal control over the X-ray flux. Finally, volumetric coverage is limited by detector size, scattered radiation, conebeam artifacts, Heel effect, and helical over-scan. We propose a new concept, multi-source inverse geometry CT, which allows CT to break through several of the above limitations. The proposed architecture has several advantages compared to third-generation CT: the detector is small and can have a high detection efficiency, the optical spot size is more consistent throughout the field-of-view, scatter is minimized even when eliminating the anti-scatter grid, the X-ray flux from each source can be modulated independently to achieve an optimal noise-dose tradeoff, and the geometry offers unlimited coverage without cone-beam artifacts. In this work we demonstrate the advantages of multi-source inverse geometry CT using computer simulations.

Metal Artifact Reduction in CT: Where Are We After Four Decades?

Methods to overcome metal artifacts in computed tomography (CT) images have been researched and developed for nearly 40 years. When X-rays pass through a metal object, depending on its size and density, different physical effects will negatively affect the measurements, most notably beam hardening, scatter, noise, and the non-linear partial volume effect. These phenomena severely degrade image quality and hinder the diagnostic power and treatment outcomes in many clinical applications. In this paper, we first review the fundamental causes of metal artifacts, categorize metal object types, and present recent trends in the CT metal artifact reduction (MAR) literature. To improve image quality and recover information about underlying structures, many methods and correction algorithms have been proposed and tested. We comprehensively review and categorize these methods into six different classes of MAR: metal implant optimization, improvements to the data acquisition process, data correction based on physics models, modifications to the reconstruction algorithm (projection completion and iterative reconstruction), and image-based post-processing. The primary goals of this paper are to identify the strengths and limitations of individual MAR methods and overall classes, and establish a relationship between types of metal objects and the classes that most effectively overcome their artifacts. The main challenges for the field of MAR continue to be cases with large, dense metal implants, as well as cases with multiple metal objects in the field of view. Severe photon starvation is difficult to compensate for with only software corrections. Hence, the future of MAR seems to be headed toward a combined approach of improving the acquisition process with dual-energy CT, higher energy X-rays, or photon-counting detectors, along with advanced reconstruction approaches. Additional outlooks are addressed, including the need for a standardized evaluation system to compare MAR methods.

Block-based iterative coordinate descent

In the context of x-ray computed tomography (CT), the iterative coordinate descent (ICD) algorithm is a reconstruction algorithm that computes image updates on a voxel-by-voxel basis [1]. This algorithm in turn can form the basis of powerful model-based iterative reconstruction frameworks for CT reconstruction [2]. In this paper, we will explore a blockbased version of ICD (B-ICD) that computes an update for a block of N voxels simultaneously while accounting for the correlation among the N voxels. Previous studies investigating grouped updates in a coordinate descent (GCD) framework include updating a group of potentially correlated or coupled voxels using an under-relaxation factor that preserves convergence [3], [4]. For the B-ICD method, however, we form and solve a linear system corresponding to a block of voxels in which we directly account for the correlation. Using this framework, we can update highly correlated voxels whereas with GCD algorithms it is preferable in terms of the resultant relaxation factors to update voxels with little to no correlation.

High Power Distributed X-ray Source

This paper summarizes the development of a distributed x-ray source with up to 60kW demonstrated instantaneous power. Component integration and test results are shown for the dispenser cathode electron gun, fast switching controls, high voltage stand-off insulator, brazed anode, and vacuum system. The current multisource prototype has been operated for over 100 hours without failure, and additional testing is needed to discover the limiting component. Example focal spot measurements and x-ray radiographs are included. Lastly, future development opportunities are highlighted.

Spatial resolution enhancement in CT iterative reconstruction

Iterative reconstruction (IR) has recently been proposed to improve multiple aspects of image quality over conventional filtered backprojection (FBP) in X-ray computed tomography (CT). FBP reconstruction and its corresponding reconstruction kernels have been optimized for decades to provide the best possible image quality. IR does not have the notion of reconstruction kernels but uses other mechanisms to change the image resolution and image noise. This paper presents one computationally efficient technique to enhance the spatial resolution of IR images reconstructed from high resolution scans, based on the introduction of an enlarged voxel footprint in the forward model, combined with a band-suppression filter designed to eliminate any undesirable over- or under-shoot artifacts that may arise from the use of the enlarged voxels. The proposed technique achieves higher spatial resolution than high resolution FBP with significantly lower noise. Results are shown on both phantom and clinical patient data.