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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Basic prerequisites for limit-cycle oscillations within a synchronously pumped passive optical nonlinear fiber-ring resonator

By taking into account Kerr nonlinearity and negative second-order dispersion, we show by numerical investigations that in a passive optical nonlinear fiber ring resonator synchronously pumped with femtosecond pulses a temporal delay via a resonator length detuning or via third-order dispersion leads to limit cycle behavior, which is represented by an oscillatory evolution of the temporal as well as the spectral pulse shape. By introducing a two-dimensional iterative map, we show that limit cycles arise due to the mutual coupling of different spectral pulse components. The resulting system behavior can be used to introduce additional adjustable frequency components into frequency combs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Adaptive schemes for incomplete quantum process tomography

We propose an iterative algorithm for incomplete quantum process tomography with the help of quantum state estimation. The algorithm, which is based on the combined principles of maximum likelihood and maximum entropy, yields a unique estimator for an unknown quantum process when one has less than a complete set of linearly independent measurement data to specify the quantum process uniquely. We apply this iterative algorithm adaptively in various situations and so optimize the amount of resources required to estimate a quantum process with incomplete data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning assisted unfolding for neutrino cross-section measurements with the OmniFold technique

The choice of unfolding method for a cross-section measurement is tightly coupled to the model dependence of the efficiency correction and the overall impact of cross-section modeling uncertainties in the analysis. A key issue is the dimensionality used in unfolding, as the kinematics of all outgoing particles in an event typically affect the reconstruction performance in a neutrino detector. OmniFold is an unfolding method that iteratively reweights a simulated dataset, using machine learning to utilize arbitrarily high-dimensional information, that has previously been applied to proton-proton and proton-electron datasets. This paper demonstrates OmniFold’s application to a neutrino cross-section measurement for the first time using a public T2K near detector simulated dataset, comparing its performance with traditional approaches using a mock data study.

Machine learning↗
DOE OSTI2020

Relevance Vector Machine Image Reconstruction Algorithm for Electrical Capacitance Tomography With Explicit Uncertainty Estimates

We present a Relevance Vector Machine (RVM) based algorithm for electrical capacitance tomography (ECT) applications that can concurrently provide image reconstruction results and uncertainty estimates about the reconstruction. To illustrate the RVM operation in ECT, we simulate typical ECT scenarios, making explicit the connection between the reconstructed pixel values and the corresponding uncertainty estimates in each case. We compare the RVM reconstruction performance with that of the Iterative Landweber Method (ILM) and the least absolute shrinkage and selection operator (LASSO) in all the considered scenarios. The results show that, in addition to the key advantage of providing uncertainty measures, RVM can achieve similar reconstruction results with either lower or similar computational complexity.

42 ENGINEERING↗
DOE OSTI2021

Spread Spectrum Symbol Detection With Blind Interference Suppression in FBMC-SS

Recent works have demonstrated Filter Bank Multicarrier Spread Spectrum (FBMC-SS) to be a robust communication scheme in the presence of high-power interferers. Existing FBMC-SS symbol detector designs based on analysis filter banks (AFB) suggest using an optimal combining scheme to suppress the interferers, necessitating some noise/interference power estimation method. In this paper, we introduce a symbol detector with blind interference suppression by extending a recently developed packet detection method. We then provide an analysis to show that the existing AFB-based symbol detector and the one proposed in this paper are equivalent in typical usage scenarios. A fully-fledged receiver design is proposed utilizing this symbol detector, with specifics presented for estimation of the channel impulse response and carrier frequency offset (CFO). We also outline a method of iterating upon the channel and CFO estimations to improve the quality of both parameters. Moreover, a modification to allow improved performance of the symbol detector at high SNR is provided. Finally, simulated performance results are presented to corroborate these findings and demonstrate the efficiency of this receiver design.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Robust Recovery of Temporally Smooth Signals From Under-Determined Multiple Measurements

In this study, we consider the problem of recovering jointly sparse vectors from underdetermined measurements that are corrupted by both additive noise and outliers. This can be viewed as the robust extension of the Multiple Measurement Vector (MMV) problem. To solve this problem, we propose two general approaches. As a benchmark, the first approach preprocesses the input for outlier removal and then employs state-of-the-art technologies for signal recovery. The second approach, as the main contribution of this paper, is based on formulation of an innovative regularized fitting problem. By solving the regularized fitting problem, we jointly remove outliers and recover the sparse vectors. Furthermore, by exploiting temporal smoothness among the sparse vectors, we improve noise robustness of the proposed approach and avoid the problem of over-fitting. Extensive numerical results are provided to illustrate the excellent performance of the proposed approach.

47 OTHER INSTRUMENTATION↗
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 OSTI2013

Motion-map constrained image reconstruction (MCIR): Application to four-dimensional cone-beam computed tomography

Purpose: Utilization of respiratory correlated four-dimensional cone-beam computed tomography (4DCBCT) has enabled verification of internal target motion and volume immediately prior to treatment. However, with current standard CBCT scan, 4DCBCT poses challenge for reconstruction due to the fact that multiple phase binning leads to insufficient number of projection data to reconstruct and thus cause streaking artifacts. The purpose of this study is to develop a novel 4DCBCT reconstruction algorithm framework called motion-map constrained image reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as projections used in a standard free breathing 3DCBCT (FB-3DCBCT) scan.Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as a combination of FB-3DCBCT and phase-specific update vector which has an associated motion-map matrix. The motion-map matrix, which is the key innovation of the MCIR algorithm, was defined as the matrix that distinguishes voxels that are moving from stationary ones. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the phase-wise sorted projections and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we evaluated both numerical phantoms and a lung cancer patient. The results were then compared with the (1) clinical FB-3DCBCT reconstructed using the FDK, (2) 4DCBCT reconstructed using the FDK, and (3) 4DCBCT reconstructed using the well-known prior image constrained compressed sensing (PICCS).Results: Examination of the MCIR algorithm showed that high phase-resolved 4DCBCT with sets of up to 20 phases using a typical FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, in comparison with other published algorithms, the image quality of the MCIR algorithm is shown to be excellent.Conclusions: This work demonstrates the potential for providing high-quality 4DCBCT during on-line image-guided radiation therapy (IGRT), without increasing the imaging dose. The results showed that (at least) 20 phase images could be reconstructed using the same projections data, used to reconstruct a single FB-3DCBCT, without streak artifacts that are caused by insufficient projections.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Simultaneous reduction of radiation dose and scatter for CBCT by using collimators

Purpose: On-board cone-beam CT (CBCT) imaging has been widely available in radiotherapy clinic for target localization. However, the extra radiation dose from CBCT is always a concern for its frequent use. Additionally, the relatively large scatter in CBCT often degrades the image quality. By using collimators, some of the X-rays can be stopped from reaching the patient and the detectors, hence both the scatter and the patient doses are simultaneously reduced. The authors show in this work that the collimated CBCT data can be reconstructed without any noticeable artifacts for certain collimator blocking ratios and blocking patterns, and the focus of this work is to study the relationship between the image quality and these two collimator factors.Methods: A CBCT system with collimators was simulated following the typical geometry used in clinic. Different collimator designs were tested by varying the size and the number of the collimator slits, and at the same time, the ratio of transmitted beams to total beams was varied from 100% to 10%, resulting in hundreds of different simulation scenarios. Lung and pelvis phantoms created from patients CT images were used in the simulations, and an iterative reconstruction algorithm using the compressed sensing technique was adopted. The image quality was examined by root mean square errors (RMSEs) and compared with the conventional CBCT images.Results: The CBCT image quality increases as the amount of beams passing through the collimators increases, and decreases as the size of the collimator slits increases. With ultra-high resolution collimators, the RMSEs were comparable to the conventional CBCT image quality until the beam transmission rate is reduced below 25%.Conclusions: Collimators can reduce the scatters and radiation dose, however, the collimated CBCT image quality is strongly dependent on both the collimator blocking ratio and the blocking pattern. To achieve image quality comparable to the conventional CBCT, the amount of information and data format must be adequate.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

MO-G-18A-01: Radiation Dose Reducing Strategies in CT, Fluoroscopy and Radiography

Advances in medical x-ray imaging have provided significant benefits to patient care. According to NCRP 160, there are more than 400 million x-ray procedures performed annually in the United States alone that contributes to nearly half of all the radiation exposure to the US population. Similar growth trends in medical x-ray imaging are observed worldwide. Apparent increase in number of medical x-ray imaging procedures, new protocols and the associated radiation dose and risk has drawn considerable attention. This has led to a number of technological innovations such as tube current modulation, iterative reconstruction algorithms, dose alerts, dose displays, flat panel digital detectors, high efficient digital detectors, storage phosphor radiography, variable filters, etc. that are enabling users to acquire medical x-ray images at a much lower radiation dose. Along with these, there are number of radiation dose optimization strategies that users can adapt to effectively lower radiation dose in medical x-ray procedures. The main objectives of this SAM course are to provide information and how to implement the various radiation dose optimization strategies in CT, Fluoroscopy and Radiography. Learning Objectives: To update impact of technological advances on dose optimization in medical imaging. To identify radiation optimization strategies in computed tomography. To describe strategies for configuring fluoroscopic equipment that yields optimal images at reasonable radiation dose. To assess ways to configure digital radiography systems and recommend ways to improve image quality at optimal dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-PIS-Exhibit Hall-01: CT Dose Optimization Technologies II

Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The imaging topic this year is CT scanner dose optimization capabilities. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Siemens‘ Commitment to the Right Dose in Computed Tomography Presentation Time: 11:15 - 11:45 AM Providing sustainable clinical results at highest patient safety: This is the challenge in medical imaging. Especially for Computed Tomography this means applying not simply the lowest, but the right dose for sound diagnostic imaging. Consequently, Siemens is committed to deliver the right dose in CT. In order to reduce radiation to the right dose, the first step is to provide the right dose technology. Through decades of research and development in CT imaging, Siemens CT has constantly introduced new ideas leading to a comprehensive portfolio of unique CARE technologies to deliver the right dose. For example automated kV adjustment based on patient size and the clinical question with CARE kV and three generations of iterative reconstruction. Based on the right dose technology, the next step is to actually scan at the right dose. For this, it is key to know the right dose targets for every examination. Siemens continuously involves CT experts to push developments further and outline how users can best adapt their procedures to the right dose. For users to know whether they met the right dose targets, it is therefore important to understand and monitor the actual absolute dose values. All scanners are delivered with defined default protocols which automatically use the available right dose technologies. Finally, to deliver the right dose not just in singular cases, but ideally to patients everywhere, organizations need then to manage dose across their institutions. Here Siemens offers the right dose management tools for administrations to analyze and document dose, to train their clinical staff and to continuously optimize the application of the right dose in clinical routine. Siemens CT is not only adhering to the ALARA principle, but is inspired by it. With CARE Right Siemens show their commitment to the right dose in CT. Toshiba Aquilion CT Dose Management Tools Presentation Time: 11:45 - 12:15 PM A practical review of Toshiba’s CT dose management technologies from the physicist’s perspective. This presentation will include an overview of Toshiba’s CT dose reduction technologies and dose safeguards. Content will include answers to frequently asked questions relating to dose management, dose tracking, CTDI measurement, ACR accreditation, ACR QC, and protocol review on Toshiba CT systems. Specific topics will include the following: Toshiba’s mechanism of tube current modulation; Exposure record format and interpretation of the values; Dose reporting and dose safeguard tools; Use of AIDR 3D iterative reconstruction; The configuration of task specific image quality target and its integration with AIDR 3D; Tips for scanning the ACR phantom with wide beam geometry; Measuring CTDI for wide beam geometry; Discussion of daily QC procedures and specifications; Tips for annual QC evaluation; Protocol management tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-A-BRD-01: Innovation in Radiation Therapy Planning I: Knowledge Guided Treatment Planning

Intensity modulated radiation therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) offer the capability of normal tissues and organs sparing. However, the exact amount of sparing is often unknown until the plan is complete. This lack of prior guidance has led to the iterative, trial and-error approach in current planning practice. Even with this effort the search for patient-specific optimal organ sparing is still strongly influenced by planner's experience. While experience generally helps in maximizing the dosimetric advantages of IMRT/VMAT, there have been several reports showing unnecessarily high degree of plan quality variability at individual institutions and amongst different institutions, even with a large amount of experience and the best available tools. Further, when physician and physicist evaluate a plan, the dosimetric quality of the plan is often compared with a standard protocol that ignores individual patient anatomy and tumor characteristic variations. In recent years, developments of knowledge models for clinical IMRT/VMAT planning guidance have shown promising clinical potentials. These knowledge models extract past expert clinical experience into mathematical models that predict dose sparing references at patient-specific level. For physicians and planners, these references provide objective values that reflect best achievable dosimetric constraints. For quality assurance, applying patient-specific dosimetry requirements will enable more quantitative and objective assessment of protocol compliance for complex IMRT planning. Learning Objectives: Modeling and representation of knowledge for knowledge-guided treatment planning. Demonstrations of knowledge-guided treatment planning with a few clinical caanatomical sites. Validation and evaluation of knowledge models for cost and quality effective standardization of plan optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 71: A 4D Multimodal Lung Phantom for Regmentation Evaluation

Segmentation and registration of medical imaging data are two processes that can be integrated (a process termed regmentation) to iteratively reinforce each other, potentially improving efficiency and overall accuracy. A significant challenge is presented when attempting to validate the joint process particularly with regards to minimizing geometric uncertainties associated with the ground truth while maintaining anatomical realism. This work demonstrates a 4D MRI, PET, and CT compatible tissue phantom with a known ground truth for evaluating registration and segmentation accuracy. The phantom consists of a preserved swine lung connected to an air pump via a PVC tube for inflation. Mock tumors were constructed from sea sponges contained within two vacuum-sealed compartments with catheters running into each one for injection of radiotracer solution. The phantom was scanned using a GE Discovery-ST PET/CT scanner and a 0.23T Phillips MRI, and resulted in anatomically realistic images. A bifurcation tracking algorithm was implemented to provide a ground truth for evaluating registration accuracy. This algorithm was validated using known deformations of up to 7.8 cm using a separate CT scan of a human thorax. Using the known deformation vectors to compare against, 76 bifurcation points were selected. The tracking accuracy was found to have maximum mean errors of −0.94, 0.79 and −0.57 voxels in the left-right, anterior-posterior and inferior-superior directions, respectively. A pneumatic control system is under development to match the respiratory profile of the lungs to a breathing trace from an individual patient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Sci—Thur PM: Imaging — 04: An iterative triple energy window (TEW) approach to cross talk correction in quantitative small animal Tc99m and In111 SPECT

Dual isotope SPECT allows simultaneous measurement of two different tracers in vivo. With In111 (emission energies of 171keV and 245keV) and Tc99m (140keV), quantification of Tc99m is degraded by cross talk from the In111 photons that scatter and are detected at an energy corresponding to Tc99m. TEW uses counts recorded in two narrow windows surrounding the Tc99m primary window to estimate scatter. Iterative TEW corrects for the bias introduced into the TEW estimate resulting from un-scattered counts detected in the scatter windows. The contamination in the scatter windows is iteratively estimated and subtracted as a fraction of the scatter-corrected primary window counts. The iterative TEW approach was validated with a small-animal SPECT/CT camera using a 2.5mL plastic container holding thoroughly mixed Tc99m/In111 activity fractions of 0.15, 0.28, 0.52, 0.99, 2.47 and 6.90. Dose calibrator measurements were the gold standard. Uncorrected for scatter, the Tc99m activity was over-estimated by as much as 80%. Unmodified TEW underestimated the Tc99m activity by 13%. With iterative TEW corrections applied in projection space, the Tc99m activity was estimated within 5% of truth across all activity fractions above 0.15. This is an improvement over the non-iterative TEW, which could not sufficiently correct for scatter in the 0.15 and 0.28 phantoms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-B-BRB-00: Optimizing the Treatment Planning Process

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi-automatic plan evaluation, (e) quality checklist for error prevention, (f) iterative process, (g) balance of speed and quality Learning Objectives: Gain familiarity with the workflow of modern treatment planning process. Understand the scope and challenges of managing modern treatment planning processes. Gain familiarity with Lean Six Sigma approaches and their implementation in the treatment planning workflow.

60 APPLIED LIFE SCIENCES↗