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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms, such that volumes quantified from scans of different reconstruction algorithms can be compared. The little difference found between the precision of FBP and iterative reconstructions could be a result of both iterative reconstruction's diminished noise reduction at the edge of the nodules as well as the loss of resolution at high noise levels with iterative reconstruction. The findings do not rule out potential advantage of IR that might be evident in a study that uses a larger number of nodules or repeated scans.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Design of smart 3D-digital X-ray microtomographic scanners for non-destructive testing of materials and components of electronic devices with a multilayered structure

The article studies the operating procedures of an X-ray microtomographic scanner and the module of reconstruction and analysis 3D-image of a test sample in particular. An algorithm for 3D-image reconstruction based on image shadow projections and mathematical methods of the processing are described. Chapter 1 describes the basic principles of X-ray tomography and general procedures of the device developed. Chapters 2 and 3 are devoted to the problem of resources saving by the system during the X-ray tomography procedure, which is achieved by preprocessing of the initial shadow projections. Preprocessing includes background noise removing from the images, which reduces the amount of shadow projections in general and increases the efficiency of the group shadow projections compression. Chapter 4 covers general procedures of defect search, which is based on vector analysis principles. In conclusion, the main applications of X-ray tomography are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

An algorithm to unveil the inner structure of objects concealed by beam divergence in radiographic image acquisition systems

Two main parameters rule the performance of an Image Acquisition System, namely, spatial resolution and contrast. For radiographic systems using cone beam arrangements, the farther the source, the better the resolution, but the contrast would diminish due to the lower statistics. A closer source would yield a higher contrast but it would no longer reproduce the attenuation map of the object, as the incoming beam flux would be reduced by unequal large divergences and attenuation factors. This work proposes a procedure to correct these effects when the object is comprised of a hull - or encased in it - possessing a shape capable to be described in analytical geometry terms. Such a description allows the construction of a matrix containing the attenuation factors undergone by the beam from the source until its final destination at each coordinate on the 2D detector. Each matrix element incorporates the attenuation suffered by the beam after its travel through the hull wall, as well as its reduction due to the square of distance to the source and the angle it hits the detector surface. When the pixel intensities of the original image are corrected by these factors, the image contrast, reduced by the overall attenuation in the exposure phase, are recovered, allowing one to see details otherwise concealed due to the low contrast. In order to verify the soundness of this approach, synthetic images of objects of different shapes, such as plates and tubes, incorporating defects and statistical fluctuation, have been generated, recorded for further comparison and afterwards processed to improve their contrast. The developed algorithm which, generates processes and plots the images has been written in Fortran 90 language. As the resulting final images exhibit the expected improvements, it therefore seemed worthwhile to carry out further tests with actual experimental radiographies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2010

Comparing implementations of penalized weighted least-squares sinogram restoration

Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix inversion into smaller coupled problems and exploited sparseness to minimize matrix operations. For the conjugate-gradient approach, the authors exploited sparseness and preconditioned the problem to speed up convergence. Results: All methods produced qualitatively and quantitatively similar images as measured by resolution-variance tradeoffs and difference images. Despite the acceleration strategies, the direct matrix-inversion approach was found to be uncompetitive with iterative approaches, with a computational burden higher by an order of magnitude or more. The iterative conjugate-gradient approach, however, does appear promising, with computation times half that of the authors' previous penalized-likelihood implementation. Conclusions: Iterative conjugate-gradient based PWLS sinogram restoration with careful matrix optimizations has computational advantages over direct matrix PWLS inversion and over penalized-likelihood sinogram restoration and can be considered a good alternative in standard-dose regimes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Visualizing nanoscale excitonic relaxation properties of disordered edges and grain boundaries in monolayer molybdenum disulfide

The ideal building blocks for atomically thin, flexible optoelectronic and catalytic devices are two-dimensional monolayer transition metal dichalcogenide semiconductors. Although challenging for two-dimensional systems, sub-diffraction optical microscopy provides a nanoscale material understanding that is vital for optimizing their optoelectronic properties. We use the ‘Campanile’ nano-optical probe to spectroscopically image exciton recombination within monolayer MoS2 with sub-wavelength resolution (60 nm), at the length scale relevant to many critical optoelectronic processes. Moreover, synthetic monolayer MoS2 is found to be composed of two distinct optoelectronic regions: an interior, locally ordered but mesoscopically heterogeneous two-dimensional quantum well and an unexpected ~300-nm wide, energetically disordered edge region. Further, grain boundaries are imaged with sufficient resolution to quantify local exciton-quenching phenomena, and complimentary nano-Auger microscopy reveals that the optically defective grain boundary and edge regions are sulfur deficient. In conclusion, the nanoscale structure–property relationships established here are critical for the interpretation of edge- and boundary-related phenomena and the development of next-generation two-dimensional optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2011

CT image construction of a totally deflated lung using deformable model extrapolation

Purpose: A novel technique is proposed to construct CT image of a totally deflated lung from a free-breathing 4D-CT image sequence acquired preoperatively. Such a constructed CT image is very useful in performing tumor ablative procedures such as lung brachytherapy. Tumor ablative procedures are frequently performed while the lung is totally deflated. Deflating the lung during such procedures renders preoperative images ineffective for targeting the tumor. Furthermore, the problem cannot be solved using intraoperative ultrasound (U.S.) images because U.S. images are very sensitive to small residual amount of air remaining in the deflated lung. One possible solution to address these issues is to register high quality preoperative CT images of the deflated lung with their corresponding low quality intraoperative U.S. images. However, given that such preoperative images correspond to an inflated lung, such CT images need to be processed to construct CT images pertaining to the lung's deflated state. Methods: To obtain the CT images of deflated lung, we present a novel image construction technique using extrapolated deformable registration to predict the deformation the lung undergoes during full deflation. The proposed construction technique involves estimating the lung's air volume in each preoperative image automatically in order to track the respiration phase of each 4D-CT image throughout a respiratory cycle; i.e., the technique does not need any external marker to form a respiratory signal in the process of curve fitting and extrapolation. The extrapolated deformation field is then applied on a preoperative reference image in order to construct the totally deflated lung's CT image. The technique was evaluated experimentally using ex vivo porcine lung. Results: The ex vivo lung experiments led to very encouraging results. In comparison with the CT image of the deflated lung we acquired for the purpose of validation, the constructed CT image was very similar. The intensity mean absolute difference between these two images was calculated to be at 1%. Tumor center as well as a number of anatomical fiducial markers were traced in different corresponding slices of the two images. The average misalignment obtained for the constructed CT image was (0.64, 0.39, 0.11) mm, which indicates a very desirable accuracy for lung brachytherapy applications. Conclusions: The image construction accuracy obtained in this research is suitable for intraoperative tasks; e.g., tumor localization and fusing with real time navigation data in lung brachytherapy. These applications involve image registration with intraoperative U.S. images in order to enhance their poor quality. The proposed technique is also useful for preoperative tasks such as planning of lung brachytherapy treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Interferences, ghost images and other quantum correlations according to stochastic optics

There are an extensive variety of experiments in quantum optics that emphasize the non-local character of the coincidence measurements recorded by spatially separated photocounters. These are the cases of ghost image and other interference experiments based on correlated photons produced in, for instance, the process of parametric down-conversion or photon cascades. We propose to analyse some of these correlations in the light of stochastic optics, a local formalism based on classical electrodynamics with added background fluctuations that simulate the vacuum field of quantum electrodynamics, and raise the following question: can these experiments be used to distinguish between quantum entanglement and classical correlations? - Highlights: Black-Right-Pointing-Pointer We analyse some quantum correlations in the light of stochastic optics. Black-Right-Pointing-Pointer We study how vacuum fluctuations can rule quantum correlations. Black-Right-Pointing-Pointer Many criteria cannot be considered a boundary between quantum and classical theories. Black-Right-Pointing-Pointer Non-locality is a misused term in relation to many observed experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Fourth-order partial differential equation noise removal on welding images

Partial differential equation (PDE) has become one of the important topics in mathematics and is widely used in various fields. It can be used for image denoising in the image analysis field. In this paper, a fourth-order PDE is discussed and implemented as a denoising method on digital images. The fourth-order PDE is solved computationally using finite difference approach and then implemented on a set of digital radiographic images with welding defects. The performance of the discretized model is evaluated using Peak Signal to Noise Ratio (PSNR). Simulation is carried out on the discretized model on different level of Gaussian noise in order to get the maximum PSNR value. The convergence criteria chosen to determine the number of iterations required is measured based on the highest PSNR value. Results obtained show that the fourth-order PDE model produced promising results as an image denoising tool compared with median filter.

42 ENGINEERING↗
DOE OSTI2016

Melt front propagation in dielectrics upon femtosecond laser irradiation: Formation dynamics of a heat-affected layer

Several studies in dielectrics have reported the presence of a thin heat-affected layer underneath the ablation crater produced by femtosecond laser irradiation. In this work, we present a time-resolved microscopy technique that is capable of monitoring the formation dynamics of this layer and apply it to the study of a phosphate glass exposed to single pulses below the ablation threshold. A few nanoseconds after laser excitation, a melt front interface can be detected, which propagates into the bulk, gradually slowing down its speed. By means of image analysis combined with optical modeling, we are able to determine the temporal evolution of the layer thickness and its refractive index. Initially, a strong transient decrease in the refractive index is observed, which partially recovers afterwards. The layer resolidifies after approximately 1 μs after excitation, featuring a maximum thickness of several hundreds of nanometers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A spectrometer for ultrashort gamma-ray pulses with photon energies greater than 10 MeV

Herein we present a design for a pixelated scintillator based gamma-ray spectrometer for non-linear inverse Compton scattering experiments. By colliding a laser wakefield accelerated electron beam with a tightly focused, intense laser pulse, gamma-ray photons up to 100 MeV energies and with few femtosecond duration may be produced. To measure the energy spectrum and angular distribution, a 33 × 47 array of cesium-iodide crystals was oriented such that the 47 crystal length axis was parallel to the gamma-ray beam and the 33 crystal length axis was oriented in the vertical direction. Using an iterative deconvolution method similar to the YOGI code, modeling of the scintillator response using GEANT4 and fitting to a quantum Monte Carlo calculated photon spectrum, we are able to extract the gamma ray spectra generated by the inverse Compton interaction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Computerized comprehensive data analysis of Lung Imaging Database Consortium (LIDC)

Purpose: Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. Methods: The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. Results: The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length {<=}20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios {>=}80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy {>=}4). Conclusions: This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

An algorithm for efficient metal artifact reductions in permanent seed implants

Purpose: In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications. Methods: The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections. Results: In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value. Conclusions: An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Calibration-free device sizing using an inverse geometry x-ray system

Purpose: Quantitative coronary angiography (QCA) can be used to support device size selection for cardiovascular interventions. The accuracy of QCA measurements using conventional x-ray fluoroscopy depends on proper calibration using a reference object and avoiding vessel foreshortening. The authors have developed a novel interventional device sizing method using the inverse geometry scanning-beam digital x-ray (SBDX) fluoroscopy system. The proposed method can measure the diameter and length of vessel segments without imaging a reference object and when vessels appear foreshortened. Methods: SBDX creates multiple tomosynthetic x-ray images corresponding to planes through the patient volume. The structures that lie in the plane are in focus and the features above and below the plane are blurred. Three-dimensional localization of the vessel edges was performed by examining the degree of blurring at each image plane. A 3D vessel centerline was created and used to determine vessel magnification and angulation relative to the image planes. Diameter measurements were performed using a model-based method and length measurements were calculated from the 3D centerline. Phantom validation was performed by measuring the diameter and length of vessel segments with nominal diameters ranging from 0.5 to 2.8 mm and nominal lengths of 42 mm. The phantoms were imaged at a range of positions between the source and the detector ({+-}16 cm relative to isocenter) and with a range of foreshortening angles (0 deg. - 75 deg.). Results: Changes in vessel phantom position created magnifications ranging from 87% to 118% relative to isocenter magnification. Average diameter errors were less than 0.15 mm. Average length measurements were within 1% (0.3 mm) of the true length. No trends were observed between measurement accuracy and magnification. Changes in vessel phantom orientation resulted in decreased apparent length down to 28% of the original nonforeshortened length. Average diameter errors were less than 0.25 mm across all vessel angulations; errors were less than 0.1 mm for smaller diameter vessels and low to moderate vessel angles. Diameter errors increased with true diameter and vessel angle relative to the image plane. Average length measurement errors were also within 1% (0.3 mm) for each angulation. Conclusions: Tomosynthetic imaging with SBDX can accurately measure dimensions of vessels in various magnifications and angulations without calibration. This method may be more accurate and convenient than conventional QCA techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Stochastic formulation of patient positioning using linac-mounted cone beam imaging with prior knowledge

Purpose: In this work, a novel stochastic framework for patient positioning based on linac-mounted CB projections is introduced. Based on this formulation, the most probable shifts and rotations of the patient are estimated, incorporating interfractional deformations of patient anatomy and other uncertainties associated with patient setup. Methods: The target position is assumed to be defined by and is stochastically determined from positions of various features such as anatomical landmarks or markers in CB projections, i.e., radiographs acquired with a CB-CT system. The patient positioning problem of finding the target location from CB projections is posed as an inverse problem with prior knowledge and is solved using a Bayesian maximum a posteriori (MAP) approach. The prior knowledge is three-fold and includes the accuracy of an initial patient setup (such as in-room laser and skin marks), the plasticity of the body (relative shifts between target and features), and the feature detection error in CB projections (which may vary depending on specific detection algorithm and feature type). For this purpose, MAP estimators are derived and a procedure of using them in clinical practice is outlined. Furthermore, a rule of thumb is theoretically derived, relating basic parameters of the prior knowledge (initial setup accuracy, plasticity of the body, and number of features) and the parameters of CB data acquisition (number of projections and accuracy of feature detection) to the expected estimation accuracy. Results: MAP estimation can be applied to arbitrary features and detection algorithms. However, to experimentally demonstrate its applicability and to perform the validation of the algorithm, a water-equivalent, deformable phantom with features represented by six 1 mm chrome balls were utilized. These features were detected in the cone beam projections (XVI, Elekta Synergy) by a local threshold method for demonstration purposes only. The accuracy of estimation (strongly varying for different plasticity parameters of the body) agreed with the rule of thumb formula. Moreover, based on this rule of thumb formula, about 20 projections for 6 detectable features seem to be sufficient for a target estimation accuracy of 0.2 cm, even for relatively large feature detection errors with standard deviation of 0.5 cm and spatial displacements of the features with standard deviation of 0.5 cm. Conclusions: The authors have introduced a general MAP-based patient setup algorithm accounting for different sources of uncertainties, which are utilized as the prior knowledge in a transparent way. This new framework can be further utilized for different clinical sites, as well as theoretical developments in the field of patient positioning for radiotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

Purpose: Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. Methods: Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. Results: The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within {approx}200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of {approx}75 mm and 370 mm, respectively). The median TRE within {approx}200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p= 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). Conclusions: Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Generation of a suite of 3D computer-generated breast phantoms from a limited set of human subject data

Purpose: The authors previously reported on a three-dimensional computer-generated breast phantom, based on empirical human image data, including a realistic finite-element based compression model that was capable of simulating multimodality imaging data. The computerized breast phantoms are a hybrid of two phantom generation techniques, combining empirical breast CT (bCT) data with flexible computer graphics techniques. However, to date, these phantoms have been based on single human subjects. In this paper, the authors report on a new method to generate multiple phantoms, simulating additional subjects from the limited set of original dedicated breast CT data. The authors developed an image morphing technique to construct new phantoms by gradually transitioning between two human subject datasets, with the potential to generate hundreds of additional pseudoindependent phantoms from the limited bCT cases. The authors conducted a preliminary subjective assessment with a limited number of observers (n= 4) to illustrate how realistic the simulated images generated with the pseudoindependent phantoms appeared. Methods: Several mesh-based geometric transformations were developed to generate distorted breast datasets from the original human subject data. Segmented bCT data from two different human subjects were used as the 'base' and 'target' for morphing. Several combinations of transformations were applied to morph between the 'base' and 'target' datasets such as changing the breast shape, rotating the glandular data, and changing the distribution of the glandular tissue. Following the morphing, regions of skin and fat were assigned to the morphed dataset in order to appropriately assign mechanical properties during the compression simulation. The resulting morphed breast was compressed using a finite element algorithm and simulated mammograms were generated using techniques described previously. Sixty-two simulated mammograms, generated from morphing three human subject datasets, were used in a preliminary observer evaluation where four board certified breast radiologists with varying amounts of experience ranked the level of realism (from 1 ='fake' to 10 ='real') of the simulated images. Results: The morphing technique was able to successfully generate new and unique morphed datasets from the original human subject data. The radiologists evaluated the realism of simulated mammograms generated from the morphed and unmorphed human subject datasets and scored the realism with an average ranking of 5.87 {+-} 1.99, confirming that overall the phantom image datasets appeared more 'real' than 'fake.' Moreover, there was not a significant difference (p > 0.1) between the realism of the unmorphed datasets (6.0 {+-} 1.95) compared to the morphed datasets (5.86 {+-} 1.99). Three of the four observers had overall average rankings of 6.89 {+-} 0.89, 6.9 {+-} 1.24, 6.76 {+-} 1.22, whereas the fourth observer ranked them noticeably lower at 2.94 {+-} 0.7. Conclusions: This work presents a technique that can be used to generate a suite of realistic computerized breast phantoms from a limited number of human subjects. This suite of flexible breast phantoms can be used for multimodality imaging research to provide a known truth while concurrently producing realistic simulated imaging data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions.Conclusions: The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗