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Digital breast tomosynthesis (DBT) provides 3D images which remove tissue overlapping and enables better cancer detection. Stationary DBT (s-DBT) uses a fixed X-ray source array to eliminate image blur associated with the x-ray tube motion and provides better image quality as well as faster scanning speed. For limited angle tomography, it is known that iterative reconstructions generally produces better images with fewer artifacts. However classical iterative tomosynthesis reconstruction methods are considerably slower than the filtered back-projection (FBP) reconstruction. The linear x-ray source array used in s-DBT enables a computationally more efficient volume reconstruction using adapted fan beam slice sampling, which transforms the 3-D cone beam reconstruction to a series of 2-D fan beam slice reconstructions. In this paper, we report the first results of the adapted fan-beam volume reconstruction (AFVR) for the s-DBT system currently undergoing clinical trial at UNC, using a simultaneous algebraic reconstruction technique (SART). An analytic breast phantom is used to quantitatively analyze the performance of the AFVR. Image quality of a CIRS biopsy phantom reconstructed using the AFVR method are compared to that using FBP algorithm with a commercial package. Our results show a significant reduction in memory usage and an order of magnitude speed increase in reconstructing speed using AFVR compared to that of classical 3-D cone beam reconstruction. We also observed that images reconstructed by AFVR with SART had a better sharpness and contrast compared to that using FBP. Preliminary results on patient images demonstrates the improved detectability of the s-DBT system over the mammography. By utilizing parallel computing with graphics processing unit (GPU), it is expected that the AFVR method will enable iterative reconstruction technique to be practical for clinical applications.

Cone beam computed tomography (CBCT) systems with rotational gantries that have standard flat panel detectors (FPD) are widely used for the 3D rendering of vascular structures using Feldkamp cone beam reconstruction algorithms. One of the inherent limitations of these systems is limited resolution (

The scattering noise artifact resulted in low-dose projection in repetitive cone-beam CT (CBCT) scans decreases the image quality and lessens the accuracy of the diagnosis. To improve the image quality of low-dose CT imaging, the statistical filtering is more effective in noise reduction. However, image filtering and enhancement during the entire reconstruction process exactly may be challenging due to high performance computing. The general reconstruction algorithm for CBCT data is the filtered back-projection, which for a volume of 512×512×512 takes up to a few minutes on a standard system. To speed up reconstruction, massively parallel architecture of current graphical processing unit (GPU) is a platform suitable for acceleration of mathematical calculation. In this paper, we focus on accelerating wavelet denoising and Feldkamp-Davis-Kress (FDK) back-projection using parallel processing on GPU, utilize compute unified device architecture (CUDA) platform and implement CBCT reconstruction based on CUDA technique. Finally, we evaluate our implementation on clinical tooth data sets. Resulting implementation of wavelet denoising is able to process a 1024×1024 image within 2 ms, except data loading process, and our GPU-based CBCT implementation reconstructs a 512×512×512 volume from 400 projection data in less than 1 minute.

A challenge in using on-board cone beam computed tomography (CBCT) to image lung tumor motion prior to radiation therapy treatment is acquiring and reconstructing high quality 4D images in a sufficiently short time for practical use. For the 1 minute rotation times typical of Linacs, severe view aliasing artifacts, including streaks, are created if a conventional phase-correlated FDK reconstruction is performed. The McKinnon-Bates (MKB) algorithm provides an efficient means of reducing streaks from static tissue but can suffer from low SNR and other artifacts due to data truncation and noise. We have added truncation correction and bilateral nonlinear filtering to the MKB algorithm to reduce streaking and improve image quality. The modified MKB algorithm was implemented on a graphical processing unit (GPU) to maximize efficiency. Results show that a nearly 4x improvement in SNR is obtained compared to the conventional FDK phase-correlated reconstruction and that high quality 4D images with 0.4 second temporal resolution and 1 mm 3 isotropic spatial resolution can be reconstructed in less than 20 seconds after data acquisition completes.

This paper presents a fast cone beam reconstruction method accelerated on the graphics processing unit (GPU). We implement the Feldkamp, Davis, and Kress (FDK) algorithm on the OpenGL graphics pipeline, which allows us to exploit the full resources and capabilities available on the GPU. The proposed method differs from previous GPU-based methods in having an RGBA packing scheme capable of directly dealing with projections without rebinning. It also reduces the amount of computation by using a data reuse scheme, which is useful to save the memory bandwidth for this memory-intensive problem. Both schemes contribute to reduce the number of rendering passes, namely the number of kernel invocations on the GPU, realizing fast cone beam reconstruction. We show some experimental results obtained on a desktop PC with an nVIDIA GeForce 8800 GTX card. As a result, the proposed method takes 8.1 seconds to reconstruct a 512 3 -voxel volume from 360 512 2 -pixel projection images. This execution time is equivalent to a 15.6-fold speedup over a CPU implementation, showing 10% higher performance as compared with a previous OpenGL-based method that requires the single-slice rebinning of projections for acceleration. With respect to non-rebinned data, our method provides approximately three times higher performance than the previous method.

This work is a feasibility study of a phase-contrast cone-beam CT (CBCT) system for ROI (region of interest) reconstruction in breast imaging that incorporates the in-line holography technique into a cone-beam CT system. A conventional CBCT scan is done first to find any suspicious lesion, followed by a phase-contrast CBCT scan of the ROI for detailed characterization. The phase-contrast in-line holographic images are generated using Fresnel theory through computer simulation, and the projected phase maps, as line integrals of the phase coefficient of the scanned breast, are retrieved using phase-attenuation duality theory. In this way the object's phase coefficient, as the object function, can be reconstructed using these projected phase maps through FDK algorithm. The reconstruction error is calculated to evaluate the accuracy of this approach. The noise property of this approach is investigated as well by adding Poisson noise to the holographic images. The projected phase maps are retrieved and the object function is reconstructed in the presence of noise. The results show that the object's phase coefficient can be reconstructed with very small reconstruction error, and the noise level can be greatly reduced compared to the conventional CBCT system. In conclusion, the phase-contrast CBCT breast imaging approach is very promising to provide better image quality and to lower x-ray dose level for tumor characterization.

Tomographic image reconstruction is computationally very demanding. In all cases the backprojection represents the performance bottleneck due to the high operational count and resulting high demand put on the memory subsystem. In this study, we present the implementation of a cone beam reconstruction algorithm on the Cell Broadband Engine (CBE) processor aimed at real-time applications. The cone-beam backprojection performance was assessed by backprojecting a half-circle scan of 512 projections of 10242 pixels into a volume of size 5123 voxels. The projections are acquired on a C-Arm scanner and directed in real time to a CBE-based platform for real-time reconstruction. The acquisition speed typically ranges between 17 and 35 projections per second. On a CBE processor clocked at 3.2 GHz, our implementation performs this task in ~13 seconds, allowing for real time reconstruction.© (2008) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Contrast agent bolus is used in angiography for vascular imaging. The bolus flow through a local region in the bolus wash-in phase can be captured by cone-beam scanning, producing a time series of projection images. During the bolus/blood equilibrium phase, circular cone-beam volume scanning produces a dataset that can be used for vessel (or bolus) volume reconstruction. From a bolus (or vessel) volume, we can depict the vessel anatomy and extract the 3D bolus passageways. For bolus velocity measurements, we need to calculate the 3D bolus pathlength and to determine the time interval indicated by the frame time of the dynamic bolus wash-in images. The cone-beam volume reconstruction allows 3D vessel depiction with isotropic grid resolution, thus facilitating the measurement of 3D vessel lumen and centerline. The timing information of the dynamic bolus flow corresponds to the frame time of the bolus wash-in images. In order to add time divisions to a 3D bolus passageway, we suggest a cone-beam reprojection scheme, which consists of vessel-centerline extraction, cone-beam reprojection, and image registration between reprojected images and wash-in projection images. With the accurate measurements of 3D pathlength and time interval, we can calculate the local blood flow in terms of velocity and flux. Simulations of bolus traveling along a sinuate vessel inside a cylinder are provided.

The three-dimensional image reconstruction process used in interventional CT imaging is computationally demanding. Implementation on general-purpose computational platforms requires a substantial time, which is undesirable during time-critical surgical and minimally invasive procedures. Field Programmable Gate Arrays (FPGA)s and Graphics Processing Units (GPU)s have been studied as a platform to accelerate 3-D imaging. FPGA and GPU devices offer a reprogrammable hardware architecture, configurable for pipelining and high levels of parallel processing to increase computational throughput, as well as the benefits of being off-the-shelf and effective 'performance-to-watt' solutions. The main focus of this paper is on the backprojection step of the image reconstruction process, since it is the most computationally intensive part. Using the popular Feldkamp-Davis-Kress (FDK) cone-beam algorithm, our studies indicate the entire 256 3 image reconstruction process can be accelerated to real or near real-time (i.e. immediately after a finished scan of 15-30 seconds duration) on a mobile X-ray C-arm system using available resources on built-in FPGA board. High resolution 512 3 image backprojection can be also accomplished within the same scanning time on a high-end GPU board comprising up to 128 streaming processors.

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 .

In a 3rd generation CT system, a single so urce projects the entire field of view (F OV) 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 directio n 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-so urce data are re-binned transaxially to multiple offset third-generation datasets. Second, data point s 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 co verage to 120mm without cone-beam artifact s, 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. Keywords: CT, RECON

The tomographic images reconstructed from cone beam projection data with a slice thickness larger than the nominal detector row width (namely thick image) is of practical importance in clinical CT imaging, such as neuro- and trauma- applications as well as applications for treatment planning in image guided radiation therapy. To get a balance optimization between image quality and computational efficiency, a cone beam filtered backprojection (CB-FBP) algorithm to reconstruct a thick image by tracking adaptively up-sampled cone beam projection of virtual reconstruction planes is proposed in this paper. Theoretically, a thick image is a weighted summation of a number of images with slice thickness corresponding to the nominal detector row width (namely thin image), and each thin image corresponds to a virtual reconstruction plane. To obtain the most achievable computational efficiency, the weighted summation has to be carried out in projection domain. However, it has been experimentally found that, to obtain a thick image with the reconstruction accuracy comparable to that of a thin image, the CB-FBP reconstruction algorithm has to be applied by tracking adaptively up-sampled cone beam projection data, which is the novelty of the proposed algorithm. The tracking process is carried out by making use of the cone beam projection data corresponding to the involved virtual reconstruction planes only, while the adaptive up-sampling process is implemented by interpolation along the z-direction at an adequate up-sampling rate. By using a helical body phantom, the performance of the proposed cone beam reconstruction algorithm, particularly its capability of suppressing artifacts, are experimentally evaluated and verified.

A typical X-ray CT scanner has a 50cm reconstruction field-of-view (FOV) which is significantly smaller than the 70cm FOV typically used for PET. When CT images are used for attenuation correction in PET, significant artifacts result when portions of the scanned object extend beyond 50 cm. In this paper, we present a reconstruction algorithm to estimate the missing projection samples so that a significantly larger reconstruction FOV can be achieved. The estimation is based on the observation that the total attenuation is a continuous function over views. The initial estimate of the projection distribution makes use of the property that the projection profile does not change abruptly as a function of the projection angle. When combined with the projection values at the location of truncation, the size and location of water cylinders that best fit these parameters are calculated. Additional adjustments are made to ensure the total attenuation of the expanded projection samples matches closely to the estimated total missing projection. The estimated projection is further blended with the mirror image of the measured projections near the location of truncation. Various phantom experiments were conducted to evaluate the proposed algorithm. Both axial and helical scans were collected on a 64-slice scanner. Results show that the proposed algorithm can restore the fidelity of the reconstruction for the portion of the object inside 50 cm FOV, and provide an adequate impression of the object outside 50cm.

Both flat-panel detectors and cylindrical detectors have been used in CT systems for data acquisition. The cylindrical detector generally offers a sampling of a transverse image plane more uniformly than does a flat-panel detector. However, in the longitudinal dimension, the cylindrical and flat-panel detectors offer similar sampling of the image space. In this work, we investigate a detector of spherical shape, which can yield uniform sampling of the 3D image space because the solid angle subtended by each individual detector bin remains unchanged. We have extended the backprojection-filtration (BPF) algorithm, which we have developed previously for cone-beam CT, to reconstruct images in cone-beam CT with a spherical detector. We also conduct computer-simulation studies to validate the extended BPF algorithm. Quantitative results in these numerical studies indicate that accurate images can be obtained from data acquired with a spherical detector by use of our extended BPF cone-beam algorithms.

The clinical goal of breast imaging is to detect tumor masses when they are as small as possible, preferably less than 10 mm in diameter. Conventional screen-film mammography is the most effective tool for the early detection of breast cancer currently available. However, conventional mammography has relatively low sensitivity for the detection of small breast cancers (under several millimeters). Specificity and the positive predictive value of mammography remain limited owing to an overlap in the appearance of benign and malignant lesions, and surrounding structure. We propose to address the limitations accompanying conventional mammography by incorporating a cone beam CT reconstruction technique with a recently developed flat panel detector (FPD). We have performed a computer simulation study and preliminary phantom studies to prove the feasibility of developing an FPD-based cone beam CT breast imaging technique for a small size normal breast phantom. In this study, we report the design and construction of a novel FPD-based cone beam breast CT scanner prototype. In addition, we present the results of phantom studies performed on our current FPD-based cone beam CT scanner prototype, which uses the same flat panel detector proposed for the cone beam breast CT scanner prototype, to predict the image performance of the novel cone beam breast CT scanner, while we are completing the construction of the system.

FDK algorithm has been known to be a popular 3D approximate computed tomography (CT) reconstruction algorithm. However, it may not provide satisfactory image quality for large cone angle. Recently, it has been improved by performing ramp filtering along the direction tangent to the helix, so to provide improved image quality for large cone angle. In this paper, we present a FDK type approximate reconstruction algorithm for gantry-tilted CT imaging. The proposed method improves FDK algorithm by filtering the projection data along a proper direction. Its filtering direction is determined by CT parameters and gantry-tilted angle. As a result, the proposed gantry-tilted reconstruction algorithm can provide more scanning flexibilities in clinical CT scanning and is efficient in computation. The performance of the proposed algorithm is evaluated with Turbell Clock phantom and Thorax phantom compared with gantry tilted FDK algorithm and a popular 2D approximate algorithm. The results show that our new algorithm can achieve better image quality than FDK algorithm and the 2D approximate algorithm for gantry-tilted CT image reconstruction.

The half-scan cone beam technique, requiring a scan for 180° plus detector width only, can help achieve both shorter scan time as well as higher exposure in each individual projection image. This purpose of this paper is to investigate whether half-scan cone beam CT technique can provide acceptable images for clinical application. The half-scan cone beam reconstruction algorithm uses modified Parker's weighting function and reconstructs from slightly more than half of the projection views for full-scan, giving out promising results. A rotation phantom, stationary gantry bench top system was built to conduct experiments to evaluate half-scan cone beam breast CT technique. A post-mastectomy breast specimen, a stack of lunch meat slices embedded with various sizes of calcifications and a polycarbonate phantom inserted with glandular and adipose tissue equivalents are imaged and reconstructed for comparison study. A subset of full-scan projection images of a mastectomy specimen were extracted and used as the half-scan projection data for reconstruction. The results show half-scan reconstruction algorithm for cone beam breast CT images does not significantly degrade image quality when compared with the images of same or even half the radiation dose level. Our results are encouraging, emphasizing the potential advantages in the use of half-scan technique for cone beam breast imaging.

With the introduction of volumetric computed tomography (VCT), many studies have been conducted on the cone beam reconstruction algorithms. Majority of the research efforts was devoted to the reduction of cone beam artifacts by designing special weighting functions that treat the projection samples differently based on their cone angles. The selection of weighting function can be quite complex due to the cone beam helical geometry and is often designed through trial-and-error. In this paper, we present a conjugate backprojection approach (CBA) that is capable of significantly reducing cone beam artifacts without the application of a pre-backprojection weighting function. Our approach utilizes CBA operation which simultaneously backprojects and interpolates conjugate sampling pairs. Unlike the conventional backprojection, the final backprojected value depends not only on the distance of these samples to the point-of-intersection, but also on the cone angles of these samples. Consequently, optimization can be performed on a pixel by pixel basis and is independent of the acquisition protocols, such as helical pitches or acquisition modes. The proposed approach is applicable to cone beam helical as well as step-and-shoot acquisitions. Extensive computer simulation and phantom experiments were conducted to demonstrate the efficacy of our approach. Results have shown that the proposed approach significantly reduces the cone beam artifacts.

The behavior of a Maximum Likelihood reconstruction algorithm applied to circular cone-beam CT data is examined. In a simulation study, it is shown that unacceptable artifacts appear, if a constant initial image is used. A start image that incorporates the borders of the reconstructed object correctly improves the situation, but artifacts remain that degrade the image quality. If the initial image is generated from a low-dose helical pre-scan, a cone-beam artifact free image is achieved.

The purpose of this study is to characterize a newly built flat panel detector (FPD)-based cone beam CT (CBCT) prototype for dynamic imaging. A CBCT prototype has been designed and constructed by completely modifying a GE HiSpeed Advantage (HSA) CT gantry, incorporating a newly acquired large size real-time FPD (Varian PaxScan 4030CB), a new x-ray generator and a dual focal spot angiography x-ray tube that allows the full coverage of the detector. During data acquisition, the x-ray tube and the FPD can be rotated on the gantry over Nx360 degrees due to integrated slip ring technology with the rotation speed of one second/revolution. With a single scan time of up to 40 seconds , multiple sets of reconstructions can be performed for dynamic studies. The upgrade of this system has been completed. The prototype was used for a series of preliminary phantom studies: different sizes of breast phantoms, a Humanoid chest phantom and scatter correction studies. The results of the phantom studies demonstrate that good image quality can be achieved with this newly built prototype.

In volumetric CT, the suppression of cone beam (CB) and helical artifacts is very challenging. At very high pitches larger than 1.5, not only artifact suppression but also maintenance of a large field of view (FOV) become even more challenging. At large helical pitches, the data redundancy corresponding to each pixel within a reconstruction FOV varies dramatically. An inappropriate dealing with the fast-varying data redundancy over pixels to be reconstructed can result in severe shading/glaring artifacts in reconstructed images and lead a clinical diagnosis impossible. One existing approach to combat the non-uniform data redundancy and extend the FOV at very high pitches is to reconstruct images on tilted planes. However, tilting a reconstruction plane can significantly impacts data flow of filtered backprojection -- the most attractive one practiced by all major CT manufacturers -- and slows down image generation speed considerably. Along with an experimental evaluation, a helical CB filtered backprojection reconstruction algorithm using three-dimensional view weighting (namely 3D view weighted CB-FBP algorithm) is proposed here. The novelty of the proposed algorithm is the 3D-nature of the weighting function, which enables the proposed algorithm to reach the optimal image qualities and provides the freedom in controlling image quality over accuracy, noise characteristics, spatial resolution and temporal resolution. Particularly, it is the 3D view weighting that enables the proposed algorithm to maintain an FOV at helical pitch larger than 1.5, which is as large as that at helical pitches below 1.0. It is believed that the proposed 3D view weighted CB-FBP algorithm is applicable to and robust over all CT imaging applications, including diagnostic imaging and dynamic imaging for functional evaluation. It is also believed that the proposed algorithm will work well for larger cone angles when more sophisticated 3D view weighting strategies are employed.

X-ray 3D rotational angiography based on C-arm systems has become a versatile and established tomographic imaging modality for high contrast objects in interventional environment. Improvements in data acquisition, e.g. by use of flat panel detectors, will enable C-arm systems to resolve even low-contrast details. However, further progress will be limited by the incompleteness of data acquisition on the conventional short-scan circular source trajectories. Cone artifacts, which result from that incompleteness, significantly degrade image quality by severe smearing and shading. To assure data completeness a combination of a partial circle with one or several line segments is investigated. A new and efficient reconstruction algorithm is deduced from a general inversion formula based on 3D Radon theory. The method is theoretically exact, possesses shift-invariant filtered backprojection (FBP) structure, and solves the long object problem. The algorithm is flexible in dealing with various circle and line configurations. The reconstruction method requires nothing more than the theoretically minimum length of scan trajectory. It consists of a conventional short-scan circle and a line segment approximately twice as long as the height of the region-of-interest. Geometrical deviations from the ideal source trajectory are considered in the implementation in order to handle data of real C-arm systems. Reconstruction results show excellent image quality free of cone artifacts. The proposed scan trajectory and reconstruction algorithm assure excellent image quality and allow low-contrast tomographic imaging with C-arm based cone-beam systems. The method can be implemented without any hardware modifications on systems commercially available today.

In this paper we present a source path for the purpose of exact cone-beam reconstruction using a C-arm X-ray imaging system. The proposed path consists of two intersecting segments, each of which is a short-scan. Any C-arm capable of a short-scan sweep can thus be used to obtain data on our proposed source path as well, since it only requires an additional sweep on a tilted plane. This tilt can be achieved by either using the propeller axis of mobile C-arms, or the vertical axis of ceiling mounted C-arms. While the individual segments are only capable of exact reconstruction in their mid-plane, we show that the combined path is capable of exact reconstruction within an entire volumetric region. In fact, we show that the largest sphere that can be captured in the field of view of the C-arm can be exactly reconstructed if the tilt between the planes is at least equal to the cone-angle of the system. For the purpose of cone-beam inversion we use a generalized cone-beam filtered backprojection algorithm (CB-FBP). The exactness of this method relies on the design of a set of redundancy weights, which we explicitly evaluate for the proposed dual short-scan source path.

In this paper we discuss image reconstruction algorithms in super-short-scan fan-beam and cone-beam computed tomography (CT). We propose a new fan-beam filtered back-projection algorithm which can obtain exact region of interest (ROI) reconstruction if and only if every projecting line passing through the ROI intersects the source trajectory, even if the scanning range is smaller than the half-scan. And we prove the algorithm is approximate when the projections are truncated. Furthermore, we expand the algorithm to cone-beam reconstruction. Then we simulate the algorithm on the computer and evaluate the noise properties of the new algorithm and the other algorithms. Numerical results in our work suggest that the new algorithm is generally less susceptible to data noise and less artifacts than the before algorithms. In particular, the new algorithm is easily and successfully expanded to cone-beam tomography when the source trajectory is a short-arc on the single circle or on the helical trajectory.

With the evolution from multi-detector-row CT to cone beam volumetric CT, to maintain reconstruction accuracy becomes more challenging. To combat the severe artifacts caused by a large cone angle, three-dimensional reconstruction algorithms have to be used in CB volumetric CT. In practice, the filtered backprojection (FBP) reconstruction algorithm is the most desirable due to its pipe-line computational structure and image generation efficiency. The first CB-FBP reconstruction algorithm is the well-known FDK algorithm that was originally derived for a circular x-ray source trajectory by heuristically extending its two-dimensional counterpart. Later on, a general CB-FBP reconstruction algorithm was derived for non-circular, such as helical, source trajectories. It has been recognized that, a filtering operation in the projection data along the tangential direction of a helical x-ray source trajectory can significantly improve the reconstruction accuracy of helical CB volumetric CT. However, the tangential filtering encounters latitudinal data truncation, resulting in degraded noise characteristics or data manipulation inefficiency. A CB-FBP reconstruction algorithm using one-dimensional rotational filtering across detector rows (namely CB-RFBP) is proposed in this manuscript. In principal, the proposed CB-RFBP reconstruction algorithm is approximate, but approaches the reconstruction accuracy that can be achieved by exact helical CB-FBP reconstruction algorithms because of the rotational filtering. Unlike exact CB-FBP reconstruction algorithms in which all redundant data are usually discarded to maintain data redundancy, the proposed CB-RFBP reconstruction algorithm makes use of all available projection data, resulting in significantly improved noise characteristics and dose efficiency. Moreover, the rotational filtering across detector rows not only survives the so-called long object problem, but also avoids latitudinal data truncation existing in other helical CB-FBP reconstruction algorithm in which a tangential filtering is carried out, providing improved noise characteristics, dose efficiency or data manipulation efficiency.

Conventional film-screen mammography is the most effective tool for the early detection of breast cancer currently available. However, conventional mammography has relatively low sensitivity to detect small breast cancers (under several millimeters) owing to an overlap in the appearances of benign and malignant lesions, and surrounding structure. The limitations accompanying conventional mammography is to be addressed by incorporating a cone beam CT imaging technique with a recently developed flat panel detector. Computer simulation and preliminary studies have been performed to prove the feasibility of developing a flat panel detector-based cone beam CT breast imaging (FPD-CBCTBI) technique. A preliminary system characterization study of flat panel detector-based cone beam CT for breast imaging was performed to confirm the findings in the computer simulation and previous phantom studies using the current prototype cone beam CT scanner. The results indicate that the CBCTBI technique effectively removes structure overlap and significantly improves the detectability of small breast tumors. More importantly, the results also demonstrate CBCTBI offers good image quality with the radiation dose level less than or equal to that of conventional mammography. The results from this study suggest that FPD-CBCTBI is a potentially powerful breast-imaging tool.

A modified Feldkamp (FDK) 3-D cone beam algorithm was developed to conduct the half-scan scheme on a flat panel detector (FPD)-based prototype CBCT system which is available in our Lab. X-ray source scans the object in a circular trajectory in the range of 180 degrees plus full cone angle rather than 360 degrees for a full scan. The redundant data is weighted by a weighting function in 3-D case based on the ones proposed by Parker1, FDK algorithm is then adopted to get the reconstruction image. The breast phantom and breast specimen are used in the experiment and the objects reconstructed from half-scan CBCT are compared with those reconstructed from full scan. The applicability of the half-scan scheme is testified in terms of image noise level, contrast resolution. The half-scan scheme is expected to improve the temporal resolution and may also reduce the patients’ X-ray dose level. The result showed an encouraging potential usage of the Half-scan CBCT in the functional 4-D CT imaging.

A novel angiography system with cone-beam reconstruction using a large-area flat panel detector (FPD), with 40x30cm active area and 2048x1536 matrixes with a 194μm pixel pitch, has been developed. We present results on a basic performance, spatial resolution and contrast detectability obtained on this angiography system with cone-beam function using the FPD, and compare with a conventional angiography system with an image intensifier (I.I.) and charge-coupled device (CCD) camera. We’d achieved a fast acquisition, 15 seconds as for a subtraction mode by rotating a ceiling suspended C-arm at a speed of 40 degrees per second, and ensured a large reconstructed columnar volume, φ250mmx180mm, by using the large-area detector. As a result of the evaluation, the 3D image acquired from the FPD system has a high spatial resolution with no distortion and good contrast detectability.

The state-of-the-art multiple detector-row CT, which usually employs fan beam reconstruction algorithms by approximating a cone beam geometry into a fan beam geometry, has been well recognized as an important modality for cardiac imaging. At present, the multiple detector-row CT is evolving into volumetric CT, in which cone beam reconstruction algorithms are needed to combat cone beam artifacts caused by large cone angle. An ECG-gated cardiac cone beam reconstruction algorithm based upon the so-called semi-CB geometry is implemented in this study. To get the highest temporal resolution, only the projection data corresponding to 180° plus the cone angle are row-wise rebinned into the semi-CB geometry for three-dimensional reconstruction. Data extrapolation is utilized to extend the z-coverage of the ECG-gated cardiac cone beam reconstruction algorithm approaching the edge of a CT detector. A helical body phantom is used to evaluate the ECG-gated cone beam reconstruction algorithm’s z-coverage and capability of suppressing cone beam artifacts. Furthermore, two sets of cardiac data scanned by a multiple detector-row CT scanner at 16 x 1.25 (mm) and normalized pitch 0.275 and 0.3 respectively are used to evaluate the ECG-gated CB reconstruction algorithm’s imaging performance. As a reference, the images reconstructed by a fan beam reconstruction algorithm for multiple detector-row CT are also presented. The qualitative evaluation shows that, the ECG-gated cone beam reconstruction algorithm outperforms its fan beam counterpart from the perspective of cone beam artifact suppression and z-coverage while the temporal resolution is well maintained. Consequently, the scan speed can be increased to reduce the contrast agent amount and injection time, improve the patient comfort and x-ray dose efficiency. Based up on the comparison, it is believed that, with the transition of multiple detector-row CT into volumetric CT, ECG-gated cone beam reconstruction algorithms will provide better image quality for CT cardiac applications.

Preliminary evaluation of large-area flat panel detectors (FPDs) indicates that FPDs have some potential advantages over film-screen and CCD-based imagers: compactness, high resolution, high frame rate, large dynamic range, small image lag (

Conventional screen film mammography is the most effective tool for the early detection of breast cancer currently available. However, conventional mammography has relatively low sensitivity for detecting small breast cancers (under several millimeters). Specificity and the positive predictive value of mammography remain limited owing to an overlap in the appearance of benign and malignant lesions, and surrounding structure. We propose to address the limitations accompanying conventional mammography by incorporating a cone beam volume CT (CBVCT) reconstruction technique with a recently developed flat panel detector. In this study, we present the results obtained from a computer simulation study and a breast-imaging phantom experimental study to find out the reconstruction accuracy of different cone beam volume scanning orbits for CBVCTBI, and to determine if different partial scan protocols (less than 360°) are appropriate for breast cancer detection. Three types of CBVCTBI scanning orbits were simulated using an uncompressed breast phantom. The reconstruction accuracy was evaluated as a function of different scanning orbits assuming reconstruction with 360° was the gold standard. The results indicate that with 180° plus cone angle orbit, the reconstruction error is below 4% that is in the acceptable range. In addition, a preliminary phantom study using both 360° and 180° plus cone angle orbits, was conducted on the current flat panel detector-based CBVCT prototype scanner. The companion CBVCT reconstruction images of an uncompressed breast-image phantom are presented.

Mice have been widely used in various areas of biomedical research such as drug development and genetic engineering. To investigate drug effect or treatment efficacy in the mouse studies, in-vivo mouse imaging modalities have been recently developed. Among various kinds of imaging modalities, micro-CT is expected to be useful in many biological applications since it provides 3-dimensional high-resolution tomographic images. In this study, we have developed a high-resolution micro-CT system using a microfocus x-ray source and a flat panel detector. The flat panel detector contains a CsI scintillator plate, a 2-dimensional photodiode array, and a 12-bit ADC. The photodiode array consists of 2400 x 2400 pixels of 50μm size. In order to improve computing speed in the micro-CT, we have also developed a distributed parallel processing system using multiple computers. The computation-intensive cone-beam reconstruction process has been divided into multiple tasks in a way that each CPU takes care of similar amount of computations. We have linked four desktop computers with dual AMD Athlon processors by Ethernet and optimized the task allocations among them. The developed parallel processing system has shown to have about eight times faster reconstruction speed. It is expected that the distributed image reconstruction technique can be a low cost solution for the in-vivo mouse imaging system.

In many clinical applications, it is necessary to tilt the gantry of an X-ray CT system with respect to the patient. Tilting the gantry introduces no complications for single-slice fan-beam systems; however, most systems today are helical multislice systems with up to 16 slices (and this number is sure to increase in the future). The image reconstruction algorithms used in multislice helical CT systems must be modified to compensate for the tilt. If they are not, the quality of reconstructed images will be poor with the presence of significant artifacts produced by the tilt. Practical helical multislice algorithms currently incorporated in today’s systems include helical fan-beam, ASSR (Advanced single-slice rebinning), and Feldkamp algorithms. This paper presents the modifications necessary to compensate for gantry tilt for the helical cone-beam Feldkamp algorithm implemented by Toshiba (referred to as TCOT for true cone-beam tomography). Unlike some of the other algorithms, gantry tilt compensation is simple and straightforward to implement with no significant increase in computational complexity. It will be shown that the effect of the gantry tilt is to introduce a lateral shift in the isocenter of the reconstructed slice of interest, which is a function of the tilt, couch speed, and view angle. This lateral shift is easily calculated and incorporated into the backprojection algorithm. The tilt-compensated algorithm is called T-TCOT. Experimental tilted-gantry data has been obtained with 8- and 16 slice Toshiba Aquilion systems, and examples of uncompensated and tilt compensated images are presented.

During the last years, three-dimensional X-ray imaging has become a well-established imaging modality, setting the golden standard for spatial resolution in three-dimensional X-ray imaging. Firstly introduced on a motorized C-arm system, it gained benefit from the high spatial resolution of the image intensifier. Using cone-beam reconstruction, it provided fast access to truly three-dimensional imaging with isotropic voxel dimensions. However, the non-rigid mechanics and the image distortion in the image intensifier required dedicated calibration processes and obligated the developers to use the most stable and reliable system in the C-arm device family. The need for system calibration also required the system to be able to reproducibly adjust the C-arm to the pre-calibrated positions, which seemed only possible with the motorized movement of a high-end system. On mobile, non-motorized C-arm systems, which are often used for guiding surgical procedures, however, 3D application has not been feasible due to the non-reproducibility of the mechanical movement. In this paper, first results regarding the feasibility of this approach are presented. The data were acquired on a Philips BV 26 surgical C-arm. This device is fully movable. The C arc is adjusted manually.

Developing and optimizing an x-ray scatter control and reduction technique is one big challenge for cone beam volume computed tomography (CBVCT) because CBVCT will be much less immune to scatter than fan-beam CT. X-ray Scatter reduces image contrast, increases image noise and introduces reconstruction error into CBVCT. To reduce scatter interference, a practical algorithm that is based upon the beam stop array technique and image sequence processing has been developed on a flat panel detector-based CBVCT prototype scanner. This paper presents beam stop array-based scatter correction algorithm and the evaluation results through phantom studies. The results indicate that the beam stop array-based scatter correction algorithm is practical and effective to reduce and correct x-ray scatter for a CBVCT imaging task.

Conventional film-screen mammography is the most effective tool for the early detection of breast cancer currently available. However, conventional mammography has relatively low sensitivity to detect small breast cancers (under several millimeters) owing to an overlap in the appearances of benign and malignant lesions, and surrounding structure. The limitations accompanying conventional mammography is to be addressed by incorporating a cone beam volume CT imaging technique with a recently developed flat panel detector. A computer simulation study has been performed to prove the feasibility of developing a flat panel detector-based cone beam volume CT breast imaging (FPD-CBVCTBI) technique. In this study, a phantom and specimen experiment is performed to confirm the findings in the computer simulation using the current prototype cone beam volume CT scanner. The results indicate that the CBVCTBI technique effectively removes structure overlap and significantly improves the detectability of small breast tumors. More importantly, the results also demonstrate the patient dose level required for FPD-based CBVCTBI to detect a small tumor (under 5 mm) and a small calcification is less than or equal to that of conventional mammography. The results from this study suggest that FPD-CBVCTBI is a potentially powerful breast-imaging tool.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Cone beam reconstruction has attracted a great deal of attention in the medical imaging community. However, high-resolution cone beam reconstruction (CBR) involves a huge set of data and very time consuming computing. It usually needs customized hardware or a large-scale computer to achieve acceptable speed. Although the Feldkamp algorithm is an approximate CBR algorithm, it is a practical and efficient 3D reconstruction algorithm and is a basic component in several exact cone-beam reconstruction algorithms (CBRA). In this paper, we present a practical implementation for high-speed CBR on a commercially available PC based on hybrid computing (HC). We implement Feldkamp CBR with multi-level acceleration. We use HC utilizing single instruction multiple data (SIMD) and making execution units (EU) in the processor work effectively. We also utilize the multi-thread and fiber support on the operating system, which automatically enable the reconstruction parallelism in the multi-processor environment, and makes data I/O to the hard disk more effective. Memory and cache access optimization is done by properly data partition. This approach was tested on an Intel Pentium III 500Mhz computer and was compared to the traditional implementation. It decreases more than 75% the filtering time for 288 pieces projections, saves more than 60% of the reconstruction time for the 5123 cube, and maintains good precision with less than 0.08% average error. Our system is cost-effective and high-speed. An effective reconstruction engine can be built with a market-available Symmetric Multi-processor (SMP) computer. This is an easy and cheap upgrade and is compatible with newer PC processors.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

In many cone beam reconstruction algorithms square geometry for the detector elements and cubic geometry for the reconstruction voxels are assumed. With such geometry the various operations in image reconstruction, notably projection and backprojection, can be carried out in the same manner at all angles, resulting in uniform image quality and ease of operation. However, in current multi-row cone beam CT systems the spacing between the detector rows is typically greater than the lateral spacing between the detector elements for the reconstruction of objects with slice thickness greater than the lateral resolutions. The asymmetric voxel dimensions and detector element dimensions introduce complications in the image reconstruction operations, and potentially non-uniform image quality. We have developed a procedure to preprocess the cone beam data detected on non-square detector elements for compatibility with cone beam reconstruction algorithms in which symmetric voxel dimensions and detector element dimensions are assumed. Complications and potential non-uniformity in image reconstruction operations are eliminated through simple scaling of the input cone beam projection data and decompression/elongation of the intermediate reconstructed image while retaining the symmetric geometry in the reconstruction algorithm. The procedure is a generic solution to cone beam image reconstruction applicable to all types of reconstruction algorithms.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper presents implementation of an algorithm termed as oblique surface reconstruction (OSR) on cone-beam multi-slice reconstruction. Simulations on several mathematical phantoms are performed. Theoretical consideration is reviewed and the reconstruction of simulated phantom data in comparison to the current standard 180# LI is presented. The OSR is shown to produce images with high quality when practical spiral cone-beam scanning utilizing the multi-slice configuration is considered.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Cone beam reconstruction has been the focus of many studies. One of the most widely referenced and used algorithms for circular trajectory is the Feldkamp algorithm. The advantage of the algorithm is its simplicity of implementation, efficiency in computation, and close resemblance to the well- known filtered backprojection algorithm for fan beam and parallel beam reconstruction. The algorithm is effective in terms of combating some of the cone beam artifacts. However, when objects with high density and non-uniform distribution are placed off the center plane (the fan beam plane), severe shading artifact will result. In the paper, we propose a two- pass cone beam reconstruction scheme. The algorithm is based on the observation that the high-density object reconstructed with the Feldkamp algorithm is accurate to a first order. The shading and streaking artifacts near the high-density objects are caused mainly by the incomplete sample of the circular trajectory. As a result, we can use the reconstructed ages with Feldkamp algorithm as the basis for error estimation. By segmenting these objects, we could recreate the cone beam artifacts by synthesizing the projection and reconstruction processing. The final images are produced by removing error images from the first-pass images.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A multitude of approximate cone-beam algorithms have been proposed suited for reconstruction of small cone angle CT data. The goal of this study is to identify a practical and efficient approximate cone-beam method, and to investigate its performance at medium cone angles associated to area detectors. Three different approximate algorithms for spiral cone-beam CT will be compared: the (pi) -method, the Multirow- Fourier-Reconstruction and the Advanced Single-Slice Rebinning method. These algorithms are different in the way how the two- dimensional detector images are filtered. In each view x-ray samples are identified which describe an approximation to a virtual reconstruction plane. The image quality of the respective reconstruction will be assessed with respect to image artifacts, the slice sensitivity profile, and the in- plane modulation transfer function. It turns out that the performance of approximate reconstruction improves as the virtual reconstruction plane better fits the spiral focus path. The Advanced Single-Slice Rebinning method using tilted reconstruction planes is a practical algorithm, providing image quality comparable to that of a single-row scanning system even with a 46 row detector at a table feed of 64 mm per rotation of the gantry.

We present a spiral scan cone beam reconstruction algorithm in which image reconstruction proceeds via backprojection in the object space. In principle the algorithm can reconstruct sectional ROI in a long object. The approach is a generalization of the cone beam backprojection technique developed by Kudo and Saito in two aspects: the resource- demanding normalization step in the Kudo and Saito's algorithm is eliminated through the technique of data combination which we published earlier, and the elimination of the restriction that the detector be big enough to capture the entire image of the ROI. Restricting the projection data to the appropriate angular range required by data combination can be accomplished by a masking process. The mask consists of a top curve and a bottom curve formed by projecting the spiral turn above and the turn below from the current source position. Because of the simplification resulting from the elimination of the normalization step, the most time-consuming operations of the algorithm can be approximated by the efficient step of line-by-line ramp filtering the cone beam image in the direction of the scan path, plus a correction term. The correction term is needed because data combination is not properly matched at the mask boundary when ramp filtering is involved. This correction term to the mask boundary effect can be computed exactly. The results of testing the algorithm on simulated phantoms are presented.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The prime motivation of this work is to devise a projection algorithm that makes the Algebraic Reconstruction Technique (ART) and related methods more efficient for routine clinical use without compromising their accuracy. While we focus mostly on a fast implementation of ART-type methods in the context of 3D cone-beam reconstruction, most of the material presented here is also applicable to speed up 2D slice reconstruction from fan-beam data. In this paper, we utilize the concepts of the splatting algorithm, which is a well known and very efficient voxel-driven projection technique for parallel projection, and devise an extension for perspective cone-beam projection that is considerably more accurate than previously outlined extensions. Since this new voxel-driven splatting algorithm must make great sacrifices with regards to computational speed, we describe a new 3D ray-driven projector that uses similar concepts than the voxel-driven projector but is considerably faster, and, at the same time, also more accurate. We conclude that with the proposed fast projection algorithm the computational cost of cone-beam ART can be reduced significantly with the added benefit of slight gains in accuracy. A further conclusion of our studies is that for parallel-beam reconstruction, on the other hand, a simple voxel-driven splatting algorithm provides for more efficient projection.

A method for 3D cone beam reconstruction of cerebral vasculature (both morphology and grayscale) from a limited number (less than 10) of digital subtraction angiographic (DSA) projections obtained with a standard biplane C-arm x-ray system is described. The reconstruction method includes geometric calibration of the source and detector orientation, spatial image distortion correction, and algebraic reconstruction technique (ART) with non- negativity constraint. Accuracy of voxel gray scale values estimated by ART is enhanced by determination of weights based on the intersection volume between a pyramidal ray and cubic voxel. The reconstruction is accelerated by retaining only the vessel containing voxels and distributed computing. Reconstruction of a phantom containing fiducial markers at known 3D locations demonstrated that the reconstructed geometry is accurate to less than a pixel width. Reconstruction is also obtained from an anatomic skull phantom with an embedded cerebral vasculature reproduction that includes an aneurysm. Three dimensional reconstruction exhibited the necessary details, both structural and grayscale.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The exact weighting function in 3D image reconstruction from 2D projections with cone beam geometry is obtained as the volume of intersection of a pyramidal ray with a cubic voxel. This intersection yields a convex polyhedron whose faces are formed by either the side of the pyramid or the voxel face. For each face of a voxel, we maintain a vertex link map. When one of the four pyramidal ray planes clips the voxel, we obtain a new face and a set of new vertices, while updating existing faces and their vertex link maps. Progressively clipping the voxel by the necessary ray planes yields the intersection polyhedron, whose faces and vertices are provided by the face list and its associated vertex link maps. To generate the weight, the volume of the polyhedron is calculated by dividing the polyhedron into tetrahedrons, whose volumes are summed. The exact calculated weights were used to reconstruct 3D vascular images from simulated data using a ROI (region of interest) limited ART (algebraic reconstruction technique). Comparing the results to those obtained from length approximation indicates that more accurate reconstruction could be achieved from the weights calculated with the new method.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

It is discovered that for circular scanning orbits a function to be reconstructed, f (, can be broken into three terms: f () = fMo(f) + fMl(f) +fN(i)' where f,,(i) represents the null space component of f (i), fci')corresponds to the reconstruction proposed by Feldkamp etal, while fM1() representsthe remaining part ofthe measurement space component, denoted as f, that is not provided in the Feldkamp reconstruction. Thus, a new cone beam reconstruction algorithm for circular scans is proposed as follows: 1) compute f) using Feldkamp algorithm; 2) compute fMtfr) using the formula developed inthis paper; and 3) estimate f4). This new algorithm has the following merits: 1) By including the correction term fMl(?),itprovides a more accurate reconstruction of f,fl) than Feldkamp algorithm; 2) It computes f(r) and fMl?) in a filtered—backprojection fashion, assuring an accurate and computationally efficient reconstruction of f4(?). For this reason, we expect that it would compare favorably in practice to Grangeat algorithm. This mathematical framework also provides a new perspective to understand the analytical relation between Grangeat algorithm and Feldkamp algorithm.

An x-ray microscope system for microtomography is under development at SUNY/Buffalo, New York. Considering the characteristics of the x-ray microscope system and the limitations of current cone-beam reconstruction algorithms, a general cone-beam image reconstruction algorithm has been developed at AMIL-ARTS. In order to study the reconstruction error characteristics of the general cone-beam algorithm, a preliminary error analysis on the algorithm is performed in this paper. The most important error source in cone-beam reconstruction is the theoretical precision limitation. Like many cone-beam reconstruction algorithms, the general cone-beam algorithm is not exact in nature. Thus, an analytic reconstruction error formula is derived which relates the error to the specimen structure and various imaging parameters. Approximately, the reconstruction error is proportional to either the distance from a voxel to the midplane or the pitch of a helix-like scanning locus, and inversely proportional to the size of the scanning locus. The reconstruction error also depends on the specimen structure. The faster the structure varies along the z direction, the larger the reconstruction error will be. Specimens are modeled as stochastic fields. Typical simulation results are then depicted and discussed.

An x-ray shadow projection microscope using a scannable point source of x-rays is under development at SUNY. The point source is generated by a focused electron beam that can be steered electromagnetically in a plane perpendicular to the optical axis of the microscope. The specimen is mounted on a rotatable mechanical stage for microtomography. An elaborate feedback system is being implemented to measure and correct the motion error of the mechanical stage. The conventional cone-beam image reconstruction algorithm suffers from two constraints. Firstly, the specimen must be contained in a sphere-like reconstruction region. Secondly, the x-ray source must be moved along a circle in the specimen coordinate system. Considering the characteristics of the x-ray microscope system of ARTS-AMIL and the limitations of the conventional cone-beam reconstruction algorithm, a general cone-beam image reconstruction algorithm is presented. The general algorithm can be applied to various scanning geometries, such as polygonal, helical, or random scanning patterns, for different reasons. In order to study the general cone-beam reconstruction algorithm, a computer simulation has been performed. With various scanning parameters, projection data were generated mathematically and then the general cone-beam reconstruction algorithm tested with the simulated data. The experimental results shows that the different kinds of scanning loci of the x-ray source consistently resulted in satisfactory 3-D reconstructed images.

The cone beam X-ray transform modelizes the measurements on new 3D medical imaging devices using 2D detectors, for instance X-ray transmission tomographs using image intensifiers or gamma-ray emission tomographs using convergent collimators. The most commonly used reconstruction algorithm performs cone beam back projection (FELDKAMP 1984). But it induces some distortions for objects far from the plane of the cone apex. We have established an exact formula between the cone beam X-ray transform and the first derivative of the 3D Radon transform (GRANGEAT 1987). It shows that the distortions are induced by the shadow zone in the Radon domain related to the planes which intersect the object but not the apex trajectory. In the Radon domain, it becomes possible to restore the missing information by interpolation. Then the reconstruction principle is to compute and to invert the first derivative of the Radon transform. In this communication, we compare these two algorithms on reconstructions performed on simulated acquisitions. We study the shape and level distortions along lines parallel to the rotation axis. We present an analysis of the axial and radial variations of the Modulation Transfer Function (MTF) and of their distortions. We conclude that the Radon transform algorithm provides a regularized solution to the distortions, with optimized computing time on modern scientific computers.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A laboratory sized X-ray projection microscope and microtomographic imaging system is being developed at SUNYAB (AMIL-ARTS). High resolution two dimensional images can be recorded rapidly using a high resolution phosphor and a cooled slow scan CCD camera. The effective source size is kept small to maximize the resolution. For this purpose the electron beam is focused onto a thin film target. Three dimensional information can be derived from the high resolution two dimensional images by generating stereo pairs or by reconstructing the complete tomographic image. Real time stereo pairs can be produced by rapidly moving the position of the electron spot between two locations on the thin film target thus irradiating the specimen with X-rays from two spatially distinct directions. For high resolution tomography or microtomography the two dimensional images are recorded for a large number of different orientations of the specimen. A cone beam reconstruction scheme based on a convolution and back projection algorithm is being developed. To optimize the experimental parameters in microtomography a variety of mathematical phantoms have been examined using computer simulation technique. The experimental results reveal the quantitative relationship between the accuracy of the reconstructed image and the experimental parameters such as object shape orientation and position. 1.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.