Zhye Yin

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.

Inverse geometry CT: The next-generation CT architecture?

We present a new system architecture for X-ray computed tomography (CT). A multi-source inverse-geometry CT scanner is composed of a large distributed X-ray source with an array of discrete electron emitters and focal spots, and a high frame-rate flat-panel X-ray detector. In this work we study the advantages and the challenges of this new architecture. We predict potential breakthroughs in volumetric coverage, dose efficiency, and spatial resolution. We also present experimental results obtained with a universal benchtop system.

Completeness map evaluation demonstrated with candidate next‐generation cardiac CT architectures

PURPOSE In this report, the authors introduce the general concept of the completeness map, as a means to evaluate the completeness of data acquired by a given CT system design (architecture and scan mode). They illustrate the utility of completeness map by applying the completeness map concept to a number of candidate CT system designs, as part of a study to advance the state-of-the-art in cardiac CT. METHODS In order to optimally reconstruct a point within a volume of interest (VOI), the Radon transform on all possible planes through that point should be measured. The authors quantified the extent to which this ideal condition is satisfied for the entire image volume. They first determined a Radon completeness number for each point in the VOI, as the percentage of possible planes that is actually measured. A completeness map is then defined as a 3D matrix of the completeness numbers for the entire VOI. The authors proposed algorithms to analyze the projection datasets in Radon space and compute the completeness number for a fixed point and apply these algorithms to various architectures and scan modes that they are evaluating. In this report, the authors consider four selected candidate architectures, operating with different scan modes, for a total of five system design alternatives. Each of these alternatives is evaluated using completeness map. RESULTS If the detector size and cone angle are large enough to cover the entire cardiac VOI, a single-source circular scan can have ≥99% completeness over the entire VOI. However, only the central z-slice can be exactly reconstructed, which corresponds to 100% completeness. For a typical single-source architecture, if the detector is limited to an axial dimension of 40 mm, a helical scan needs about five rotations to form an exact reconstruction region covering the cardiac VOI, while a triple-source helical scan only requires two rotations, leading to a 2.5x improvement in temporal resolution. If the source and detector of an inverse-geometry (IGCT) system have the same axial extent, and the spacing of source points in the axial and transaxial directions is sufficiently small, the IGCT can also form an exact reconstruction region for the cardiac VOI. If the VOI can be covered by the x-ray beam in any view, a composite-circling scan can generate an exact reconstruction region covering the VOI. CONCLUSIONS The completeness map evaluation provides useful information for selecting the next-generation cardiac CT system design. The proposed completeness map method provides a practical tool for analyzing complex scanning trajectories, where the theoretical image quality for some complex system designs is impossible to predict, without yet-undeveloped reconstruction algorithms.

Parametric boundary reconstruction algorithm for industrial CT metrology application

High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.

Multi-source inverse-geometry CT: From system concept to research prototype

Third-generation CT architectures are approaching fundamental limits. Dose-efficiency is limited by finite detector efficiency and by limited control over the X-ray flux spatial profile. Increasing the volumetric coverage comes with increased scattered radiation, cone-beam artifacts, Heel effect, wasted dose and cost. Spatial resolution is limited by focal spot size and detector cell size. Temporal resolution is limited by mechanical constraints, and alternative geometries such as electron-beam CT and dual-source CT come with severe tradeoffs in terms of image quality, dose-efficiency and complexity. The concept of multi-source inverse-geometry CT (IGCT) breaks through several of the above limitations [1-3], promising a low-dose high image quality volumetric CT architecture. In this paper, we present recent progress with the design and integration efforts of the first gantry-based multi-source CT scanner.

3D analytic cone-beam reconstruction for less than a full scan using a multi-source CT system

In a 3rd generation CT system, a single source projects the entire held of view (FOV) onto a large detector opposite the source. In multi-source CT imaging, a multitude of sources sequentially project a part of the FOV on a much smaller detector. These sources may be distributed in both the trans-axial and axial directions in order to jointly cover the entire FOV. For a full scan case, scan data from multiple sources in the axial direction provide complementary information. We previously proposed window-based 3D analytic cone-beam reconstruction and showed that multi-source CT can extend the axial scan coverage to 100mm without cone-beam artifacts. However for less than a full scan case, conjugate rays are not available most of time. We propose a cone-angle dependent weighting approach to combine multi-source data from less than full scan. We compute the amount of contribution from each longitudinal source to the each voxel by considering the X-ray beam collimation, the cone-angle from each source and the geometrical relationship between sources. The proposed techniques successfully reduce artifacts as illustrated by the experiments.

Analytical cone-beam reconstruction using a multi-source inverse geometry CT system

In a 3rd generation CT system, a single source projects the entire field of view (FOV) onto a large detector opposite the source. In multi-source CT imaging, a multitude of sources sequentially project a part of the FOV on a much smaller detector. These sources may be distributed in both the trans-axial and axial directions in order to jointly cover the entire FOV. Scan data from multiple sources in the axial direction provide complementary information, which is not available in a conventional single-source CT system. In this work, an analytical 3D cone-beam reconstruction algorithm for multi-source CT is proposed. This approach has three distinctive features. First, multi-source data are re-binned transaxially to multiple offset third-generation datasets. Second, data points in sinograms from multiple source sets are either accepted or rejected for contribution to the backprojection of a given voxel. Third, instead of using a ramp filter, a Hilbert transform is combined with a parallel derivative to form the filtering mechanism. Phantom simulations are performed using a multi-source CT geometry and compared to conventional 3rd generation CT geometry. We show that multi-source CT can extend the axial scan coverage to 120mm without cone-beam artifacts, while a third-generation geometry results in compromised image quality at 60mm of axial coverage. Moreover, given that the cone-angle in the proposed geometry is limited to 7 degrees, there are no degrading effects such as the Heel effect and scattered radiation, unlike in a third-generation geometry with comparable coverage. An additional benefit is the uniform flux profile resulting in uniform image noise throughout the FOV and a uniform dose absorption profile.

3D analytic cone-beam reconstruction for multiaxial CT acquisitions

A conventional 3rd generation Computed Tomography (CT) system with a single circular source trajectory is limited in terms of longitudinal scan coverage since extending the scan coverage beyond 40 mm results in significant cone-beam artifacts. A multiaxial CT acquisition is achieved by combining multiple sequential 3rd generation axial scans or by performing a single axial multisource CT scan with multiple longitudinally offset sources. Data from multiple axial scans or multiple sources provide complementary information. For full-scan acquisitions, we present a window-based 3D analytic cone-beam reconstruction algorithm by tessellating data from neighboring axial datasets. We also show that multi-axial CT acquisition can extend the axial scan coverage while minimizing cone-beam artifacts. For half-scan acquisitions, one cannot take advantage of conjugate rays. We propose a cone-angle dependent weighting approach to combine multi-axial half-scan data. We compute the relative contribution from each axial dataset to each voxel based on the X-ray beam collimation, the respective cone-angles, and the spacing between the axial scans. We present numerical experiments to demonstrate that the proposed techniques successfully reduce cone-beam artifacts at very large volumetric coverage.

Projection-based dose metric: accuracy testing and applications for CT design

The purpose of this study was to develop and validate a projection-based dose metric that enables computationally efficient dose estimation. The two physical quantities determining dose, absorbed energy and mass, were estimated in projection space. The absorbed energy was estimated using the difference between the imparted energy and detected energy. The mass was estimated using the area under the attenuation profile. A series of phantom simulations were conducted to test the metric’s applicability for multi-material phantoms, different kVp settings, and bowtie filters. Projection-based dose estimates were benchmarked against results from the Monte Carlo (MC) simulation. The projection-based dose metric shows a strong linear correlation with MC dose estimates (R2 > 0.96). The prediction errors for projection-based dose metric are below 14%. This study demonstrates a computationally efficient and relatively accurate dose estimation method based on the projection data. It further suggests the possibility to achieve real-time and patient-specific dose optimization when applied prior to a CT scan.

Cardiac CT: A system architecture study.

BACKGROUND We are interested in exploring dedicated, high-performance cardiac CT systems optimized to provide the best tradeoff between system cost, image quality, and radiation dose. OBJECTIVE We sought to identify and evaluate a broad range of CT architectures that could provide an optimal, dedicated cardiac CT solution. METHODS We identified and evaluated thirty candidate architectures using consistent design choices. We defined specific evaluation metrics related to cost and performance. We then scored the candidates versus the defined metrics. Lastly, we applied a weighting system to combine scores for all metrics into a single overall score for each architecture. CT experts with backgrounds in cardiovascular radiology, x-ray physics, CT hardware and CT algorithms performed the scoring and weighting. RESULTS We found nearly a twofold difference between the most and the least promising candidate architectures. Architectures employed by contemporary commercial diagnostic CT systems were among the highest-scoring candidates. We identified six architectures that show sufficient promise to merit further in-depth analysis and comparison. CONCLUSION Our results suggest that contemporary diagnostic CT system architectures outperform most other candidates that we evaluated, but the results for a few alternatives were relatively close. We selected six representative high-scoring candidates for more detailed design and further comparative evaluation.