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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality for breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Human factors case study: An iterative approach to verifying and validating a new suite of reactor inspection and maintenance tooling - 177

An iterative approach was taken to perform the HF Verification and Validation (V and V) activities for a complex set of reactor inspection and maintenance tooling equipment known as the Bruce Reactor Inspection and Maintenance System (BRIMS). This paper is divided into the verification activities (of Human System Information Task Support and Design verifications) and the validation activities. The validation method used a graded approach by breaking validation activities into early usability testing and high fidelity validations. Early usability testing, allowed for issues and design concepts to be identified and explored. High fidelity validation activities tested that the final design requirements and operational goals of the system were met in the production equipment. The validation method has been described in detail by depicting the following: task selection criteria, tools, performance measures and data collection. Validation results demonstrate the benefits of the graded approach as issues were to be identified early in the design process, improvements were made during detailed design and additional testing could confirm that issues were resolved prior to commissioning. To capture and share the success of this iterative V and V approach lessons learned have been created for use in future V and V projects. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Quantitative cone-beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

Purpose: Quantitative cone-beam CT (CBCT) imaging is on increasing demand for high-performance image guided radiation therapy (IGRT). However, the current CBCT has poor image qualities mainly due to scatter contamination. Its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a correction method using planning CT (pCT) as the prior knowledge. Promising phantom results have been obtained on a tabletop CBCT system, using a correction scheme with rigid registration and without iterations. More challenges arise in clinical implementations of our method, especially because patients have large organ deformation in different scans. In this paper, we propose an improved framework to extend our method from bench to bedside by including several new components. Methods: The basic principle of our correction algorithm is to estimate the primary signals of CBCT projections via forward projection on the pCT image, and then to obtain the low-frequency errors in CBCT raw projections by subtracting the estimated primary signals and low-pass filtering. We improve the algorithm by using deformable registration to minimize the geometry difference between the pCT and the CBCT images. Since the registration performance relies on the accuracy of the CBCT image, we design an optional iterative scheme to update the CBCT image used in the registration. Large correction errors result from the mismatched objects in the pCT and the CBCT scans. Another optional step of gas pocket and couch matching is added into the framework to reduce these effects. Results: The proposed method is evaluated on four prostate patients, of which two cases are presented in detail to investigate the method performance for a large variety of patient geometry in clinical practice. The first patient has small anatomical changes from the planning to the treatment room. Our algorithm works well even without the optional iterations and the gas pocket and couch matching. The image correction on the second patient is more challenging due to the effects of gas pockets and attenuating couch. The improved framework with all new components is used to fully evaluate the correction performance. The enhanced image quality has been evaluated using mean CT number and spatial nonuniformity (SNU) error as well as contrast improvement factor. If the pCT image is considered as the ground truth, on the four patients, the overall mean CT number error is reduced from over 300 HU to below 16 HU in the selected regions of interest (ROIs), and the SNU error is suppressed from over 18% to below 2%. The average soft-tissue contrast is improved by an average factor of 2.6. Conclusions: We further improve our pCT-based CBCT correction algorithm for clinical use. Superior correction performance has been demonstrated on four patient studies. By providing quantitative CBCT images, our approach significantly increases the accuracy of advanced CBCT-based clinical applications for IGRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Applying Nonlinear Diffusion Acceleration to Fixed-Source Problems with Anisotropic Scattering - Paper 15

Work over the last several years has demonstrated the impressive performance gains that can be attained by using Moment-Based Acceleration (MBA), or High-Order/Low-Order (HOLO), methods in a variety of transport applications. In the field of neutronics, Nonlinear Diffusion Acceleration (NDA) has been used to accelerate the solution to the fixed-source problem and the k-eigenvalue problem. These methods efficiently move a major portion of the computational work out of the full phase-space (high-order (HO)) domain into a reduced phase-space (low-order (LO)) setting. In previous implementations, NDA has only been applied to isotropic scattering problems. In this paper, we will extend this methodology to anisotropic scattering. This initial work on anisotropic scattering will focus on the 1-D multi-group neutron transport equation. This summary focuses on a fixed-source problem, but the extension to criticality problems is straight-forward via NDA-NCA. Within this paper, we have described a method for extending Nonlinear Diffusion Acceleration to solve problems with anisotropic scattering. We demonstrated that a consistent low-order system, resembling the low-order system from, could be constructed. We demonstrated that the NDA method performed exceptionally in the presence of anisotropic scattering. NDA reduced the number of iterations required to meet the convergence tolerance by a factor of 500 over source iteration for a one fixed-source problem and by 3.5-50 x for the Henyey-Greenstein problems. This method is equally well-suited for eigenvalue problems. The NDA method allows us to transition the eigenvalue iteration to the low-order domain.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Multiarea Distribution System State Estimation via Distributed Tensor Completion

Here, this paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

The feasibility study and characterization of a two-dimensional diode array in “magic phantom” for high dose rate brachytherapy quality assurance

Purpose: High dose rate (HDR) brachytherapy is a radiation treatment technique capable of delivering large dose rates to the tumor. Radiation is delivered using remote afterloaders to drive highly active sources (commonly {sup 192}Ir with an air KERMA strength range between 20 000 and 40 000 U, where 1 U = 1 μGy m{sup 2}/h in air) through applicators directly into the patient's prescribed region of treatment. Due to the obvious ramifications of incorrect treatment while using such an active source, it is essential that there are methods for quality assurance (QA) that can directly and accurately verify the treatment plan and the functionality of the remote afterloader. This paper describes the feasibility study of a QA system for HDR brachytherapy using a phantom based two-dimensional 11 × 11 epitaxial diode array, named “magic phantom.”Methods: The HDR brachytherapy treatment plan is translated to the phantom with two rows of 10 (20 in total) HDR source flexible catheters, arranged above and below the diode array “magic plate” (MP). Four-dimensional source tracking in each catheter is based upon a developed fast iterative algorithm, utilizing the response of the diodes in close proximity to the {sup 192}Ir source, sampled at 100 ms intervals by a fast data acquisition (DAQ) system. Using a {sup 192}Ir source in a solid water phantom, the angular response of the developed epitaxial diodes utilized in the MP and also the variation of the MP response as a function of the source-to-detector distance (SDD) were investigated. These response data are then used by an iterative algorithm for source dwelling position determination. A measurement of the average transit speed between dwell positions was performed using the diodes and a fast DAQ.Results: The angular response of the epitaxial diode showed a variation of 15% within 360°, with two flat regions above and below the detector face with less than 5% variation. For SDD distances of between 5 and 30 mm the relative response of the epitaxial diodes used in the MP is in good agreement (within 8%) with radial dose function measurements found within the TG-43 protocol, with SDD of up to 70 mm showing a 40% over response. A method for four-dimensional localization of the HDR source was developed, allowing the source dwell position to be derived within 0.50 mm of the expected position. An estimation of the average transit speed for varying step sizes was determined and was found to increase from (12.8 ± 0.3) up to (38.6 ± 0.4) cm/s for a step size of 2.5 and 50 mm, respectively.Conclusions: Our characterization of the designed QA “magic phantom” with MP in realistic HDR photon fields demonstrates the promising performance for real-time source position tracking in four dimensions and measurements of transit times. Further development of this system will allow a full suite for QA in HDR brachytherapy and analysis, and for future in vivo tracking.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Capturing the 'Representative Person' Using Exposure Equations and Input Variable Distributions - 18416

Radiological performance assessments (PAs) for radioactive waste employ the concept of future human receptors, or persons potentially exposed to radiation releases. The International Commission on Radiological Protection (ICRP) has defined the 'representative person' as a receptor, to replace the earlier concept of an 'average member of the critical group', for use in individual dose assessments and comparisons to regulatory criteria. A representative person can be assessed in PAs by defining a critical group, which is a relatively highly exposed subpopulation; and then estimating average exposures, doses, and risks for that group. Probabilistic PA models employ probability distributions to characterize uncertainty in exposure characteristics/variables at a scale aligned with contaminant transport and other aspects of the PA model. The concept of a representative person from a critical group, in the context of the first stage of an iterative approach and a probabilistic PA model, is illustrated using a receptor scenario and a set of exposure equations that incorporate probability distributions for input variables. Different scenarios may require different equations and distributions, but the approach taken is broadly generalizable. PA practitioners and regulators may benefit from such a generalizable method, as it may simplify approaches as well as facilitate reviews and comparisons between different PAs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Scalable Asynchronous Domain Decomposition Solvers

We discuss how parallel implementations of linear iterative solvers generally alternate between phases of data exchange and phases of local computation. Increasingly large problem sizes and more heterogeneous compute architectures make load balancing and the design of low latency network interconnects that are able to satisfy the communication requirements of linear solvers very challenging tasks. In particular, global communication patterns such as inner products become increasingly limiting at scale. We explore the use of asynchronous communication based on one-sided Message Passing Interface primitives in the context of domain decomposition solvers. In particular, a scalable asynchronous two-level Schwarz method is presented. We discuss practical issues encountered in the development of a scalable solver and show experimental results obtained on a state-of-the-art supercomputer system that illustrate the benefits of asynchronous solvers in load balanced as well as load imbalanced scenarios. Using the novel method, we can observe speedups of up to four times over its classical synchronous equivalent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

TU-EF-304-07: Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Proton Therapy

Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical usages.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRA-02: Electromagnetic Tracking in Brachytherapy as An Advanced Modality for Treatment Quality Assurance

Purpose: To present the use of Electromagnetic Tracking (EMT) for quality assurance in brachytherapy by means of phantom studies and to assess the clinical applicability of EMT during HDR breast brachytherapy. Methods: An EMT system was investigated to examine its suitability for clinical applications in brachytherapy. A field generator served as electromagnetic field emitter. Sensors (magnetic sensitive only), connected to a control unit, were used and their respective position and orientation inside a pre-defined measurement volume (500 mm cube length) determined. Up to three 6DoF sensors were placed on the phantom’s surface to obtain additional reference coordinates used to derive relative measured positions of a smaller 5DoF sensor inserted in the 6F catheters of the implant. The catheters were successively measured by manual displacement of the sensor at ∼40 mm/s. The measured catheter tracks, acquired multiple times at various locations (CT and treatment room), were smoothed, divided into intervals (2.5 mm dwell step size), registered (rigid Iterative Closest Point transformation) and compared against the known phantom geometry. Results: The reference coordinates were used to exclude the influence of external (e.g., respiratory-induced) motion. Precision tests in a clinical setting showed variances below 1 mm (translational) and 1° (rotational), respectively. Our method for catheter reconstruction preserved the length of the tracked catheter (within 1 mm). The measured tracking accuracy was 1±0.3 mm (maximum: 2 mm). The results are less accurate in environments potentially interfering with the magnetic field, e.g., in the vicinity of ferromagnetic table components. Conclusion: Our EMT system is able to perform reproducible and accurate catheter tracking and reconstruction. Currently, measurements of the implant geometry in HDR breast treatments are initiated. Online implant monitoring by means of EM tracking may be a first step towards advanced brachytherapy treatment QA. The study was financially supported by ELEKTA | Nucletron. There are no further disclosures and conflicts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition

This paper proposes a model-free method for distribution system state estimation based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A third-order tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. To demonstrate the efficacy of the developed algorithm, numerical simulations are carried out using an IEEE test system.

alternating direction method of multipliers↗
DOE OSTI2013

Solving the parquet equations for the Hubbard model beyond weak coupling

We find that imposing crossing symmetry in the iteration process considerably extends the range of convergence for solutions of the parquet equations for the Hubbard model. When crossing symmetry is not imposed, the convergence of both simple iteration and more complicated continuous loading (homotopy) methods is limited to high temperatures and weak interactions. We modify the algorithm to impose the crossing symmetry without increasing the computational complexity. We also imposed time reversal and a subset of the point group symmetries, but they did not further improve the convergence. We elaborate the details of the latency hiding scheme which can significantly improve the performance in the computational implementation. With these modifications, stable solutions for the parquet equations can be obtained by iteration more quickly even for values of the interaction that are a significant fraction of the bandwidth and for temperatures that are much smaller than the bandwidth. This may represent a crucial step towards the solution of two-particle field theories for correlated electron models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-F-I-54: Spatial Resolution Studies in Proton CT Using a Phase-II Prototype Head Scanner

Purpose: To characterize the modulation transfer function (MTF) of the pre-clinical (phase II) head scanner developed for proton computed tomography (pCT) by the pCT collaboration. To evaluate the spatial resolution achievable by this system. Methods: Our phase II proton CT scanner prototype consists of two silicon telescopes that track individual protons upstream and downstream from a phantom, and a 5-stage scintillation detector that measures a combination of the residual energy and range of the proton. Residual energy is converted to water equivalent path length (WEPL) of the protons in the scanned object. The set of WEPL values and associated paths of protons passing through the object over a 360° angular scan is processed by an iterative parallelizable reconstruction algorithm that runs on GP-GPU hardware. A custom edge phantom composed of water-equivalent polymer and tissue-equivalent material inserts was constructed. The phantom was first simulated in Geant4 and then built to perform experimental beam tests with 200 MeV protons at the Northwestern Medicine Chicago Proton Center. The oversampling method was used to construct radial and azimuthal edge spread functions and modulation transfer functions. The spatial resolution was defined by the 10% point of the modulation transfer function in units of lp/cm. Results: The spatial resolution of the image was found to be strongly correlated with the radial position of the insert but independent of the relative stopping power of the insert. The spatial resolution varies between roughly 4 and 6 lp/cm in both the the radial and azimuthal directions depending on the radial displacement of the edge. Conclusion: The amount of image degradation due to our detector system is small compared with the effects of multiple Coulomb scattering, pixelation of the image and the reconstruction algorithm. Improvements in reconstruction will be made in order to achieve the theoretical limits of spatial resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Imaging of cardiac perfusion of free-breathing small animals using dynamic phase-correlated micro-CT

Purpose:Mouse models of cardiac diseases have proven to be a valuable tool in preclinical research. The high cardiac and respiratory rates of free breathing mice prohibit conventional in vivo cardiac perfusion studies using computed tomography even if gating methods are applied. This makes a sacrification of the animals unavoidable and only allows for the application of ex vivo methods. Methods: To overcome this issue the authors propose a low dose scan protocol and an associated reconstruction algorithm that allows for in vivo imaging of cardiac perfusion and associated processes that are retrospectively synchronized to the respiratory and cardiac motion of the animal. The scan protocol consists of repetitive injections of contrast media within several consecutive scans while the ECG, respiratory motion, and timestamp of contrast injection are recorded and synchronized to the acquired projections. The iterative reconstruction algorithm employs a six-dimensional edge-preserving filter to provide low-noise, motion artifact-free images of the animal examined using the authors' low dose scan protocol. Results: The reconstructions obtained show that the complete temporal bolus evolution can be visualized and quantified in any desired combination of cardiac and respiratory phase including reperfusion phases. The proposed reconstruction method thereby keeps the administered radiation dose at a minimum and thus reduces metabolic inference to the animal allowing for longitudinal studies. Conclusions: The authors' low dose scan protocol and phase-correlated dynamic reconstruction algorithm allow for an easy and effective way to visualize phase-correlated perfusion processes in routine laboratory studies using free-breathing mice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Characterization of a constrained paired-view technique in iterative reconstruction for breast tomosynthesis

Purpose: The order in which the projection views are employed in the reconstruction of tomosynthesis by iterative algorithms, such as simultaneous algebraic reconstruction technique and maximum likelihood, has a strong effect on the rate of convergence, accuracy, and the edge-blurring artifacts in the reconstructed image. The purpose of this investigation was to characterize and evaluate the effects of ordering schemes on image quality for breast tomosynthesis reconstruction and to explore a new constrained paired-view technique that could provide reduction of reconstruction artifacts. In this work, the authors compared several different ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. Furthermore, a new normalization method is presented. It produces more accurate reconstructions with reduced artifacts comparing to the standard method of sequential ordering.Methods: In addition to visual assessment of image quality, several indices such as the signal-difference-to-noise ratio, the artifact-spread function, and the lesion detectability (d{sup ′}) were computed to quantitatively evaluate the effect of ordering scheme. The sets of breast tomosynthesis projection images were simulated for reconstruction; one set had uniform background (white noise only) and the other two contained both anatomic background and quantum noise. Clinical breast images were also studied for comparison.Results: The authors have quantified the image quality in reconstructed slices for a range of tumor sizes. The authors’ proposed method provides better performance for all of the metrics tested (contrast, d{sup ′}, and the level of artifacts) both for the uniform phantom case and in the presence of anatomical structure.Conclusions: The paired projection normalization provides better performance in the image quality of the reconstructed slices, and results in a lower level of artifacts in the Z direction. This implies that even a relatively simple method like the “side-to-side” sequence, which pairs two symmetrical projections with equal angular distance from the central projection, would achieve better reconstructed image quality than the conventional “step-by-step” method, which uses sequential projections one after another.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Automated segmentation of dental CBCT image with prior-guided sequential random forests

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT. Methods: In this paper, the authors present a new automatic segmentation method to address these problems. Specifically, the authors first employ a majority voting method to estimate the initial segmentation probability maps of both mandible and maxilla based on multiple aligned expert-segmented CBCT images. These probability maps provide an important prior guidance for CBCT segmentation. The authors then extract both the appearance features from CBCTs and the context features from the initial probability maps to train the first-layer of random forest classifier that can select discriminative features for segmentation. Based on the first-layer of trained classifier, the probability maps are updated, which will be employed to further train the next layer of random forest classifier. By iteratively training the subsequent random forest classifier using both the original CBCT features and the updated segmentation probability maps, a sequence of classifiers can be derived for accurate segmentation of CBCT images. Results: Segmentation results on CBCTs of 30 subjects were both quantitatively and qualitatively validated based on manually labeled ground truth. The average Dice ratios of mandible and maxilla by the authors’ method were 0.94 and 0.91, respectively, which are significantly better than the state-of-the-art method based on sparse representation (p-value < 0.001). Conclusions: The authors have developed and validated a novel fully automated method for CBCT segmentation.

61 RADIATION PROTECTION AND DOSIMETRY↗