Synthetic Tomography Research Articles

Geodesic Convolutional Neural Network Characterization of Macro-Porous Latent Thermal Energy Storage

Abstract High-temperature latent heat thermal energy storage with metallic alloy phase change materials (PCMs) utilize the high latent heat and high thermal conductivity to gain a competitive edge over existing sensible and latent storage technologies. Novel macroporous latent heat storage units can be used to enhance the limiting convective heat transfer between the heat transfer fluid and the PCM to attain higher power density while maintaining high energy density. 3D monolithic percolating macroporous latent heat storage unit cells with random and ordered substructure topology were created using synthetic tomography data. Full 3D thermal computational fluid dynamics (CFD) simulations with phase change modeling was performed on 1000+ such structures using effective heat capacity method and temperature- and phase-dependent thermophysical properties. Design parameters, including transient thermal and flow characteristics, phase change time and pressure drop, were extracted as output scalars from the simulated charging process. As such structures cannot be parametrized meaningfully, a mesh-based Geodesic Convolutional Neural Network (GCNN) designed to perform direct convolutions on the surface and volume meshes of the macroporous structures was trained to predict the output scalars along with pressure, temperature, velocity distributions in the volume, and surface distributions of heat flux and shear stress. An Artificial Neural Network (ANN) using macroscopic properties—porosity, surface area, and two-point surface-void correlation functions—of the structures as inputs was used as a standard regressor for comparison. The GCNN exhibited high prediction accuracy of the scalars, outperforming the ANN and linear/exponential fits, owing to the disentangling property of GCNNs where predictions were improved by the introduction of correlated surface and volume fields. The trained GCNN behaves as a coupled CFD-heat transfer emulator predicting the volumetric distribution of temperature, pressure, velocity fields, and heat flux and shear stress distributions at the PCM–HTF interface. This deep learning based methodology offers a unique, generalized, and computationally competitive way to quickly predict phase change behavior of high power density macroporous structures in a few seconds and has the potential to optimize the percolating macroporous unit cells to application specific requirements.

Resolving Continental Magma Reservoirs With 3D Surface Wave Tomography

AbstractSurface wave tomography is widely used to improve our understanding of continental magma reservoirs that may be capable of fueling explosive volcanic eruptions. However, traditional surface wave tomography based on inversions for phase velocity maps and locally 1D shear velocity may have difficulty resolving strong 3D low‐velocity anomalies associated with crustal magma reservoirs. Here, we perform synthetic tomography experiments based on 3D seismic waveform simulations to understand how the limitations of surface wave tomography could affect interpretations of tomography in volcanic settings. We focus our modeling on the Yellowstone volcanic system, one of the largest and most thoroughly studied continental magmatic systems, and explore scenarios in which the maximum shear velocity anomaly associated with the crustal magma reservoir ranges between −10% and −66%. We find that even with the well‐instrumented setting near Yellowstone, the recovered shear velocity anomalies in the mid‐to‐upper crust are severely diminished due to the small spatial scale of the reservoir with respect to the seismic wavelengths that sample it. In particular, recovered VS anomalies could be reduced by a factor of two or more, implying that the inferred melt fraction of large‐scale continental magma reservoirs may be considerably underestimated.

Characterising 18F-fluciclovine uptake in breast cancer through the use of dynamic PET/CT imaging

Background18F-fluciclovine is a synthetic amino acid positron emission tomography (PET) radiotracer that is approved for use in prostate cancer. In this clinical study, we characterised the kinetic model best describing the uptake of 18F-fluciclovine in breast cancer and assessed differences in tracer kinetics and static parameters for different breast cancer receptor subtypes and tumour grades.MethodsThirty-nine patients with pathologically proven breast cancer underwent 20-min dynamic PET/computed tomography imaging following the administration of 18F-fluciclovine. Uptake into primary breast tumours was evaluated using one- and two-tissue reversible compartmental kinetic models and static parameters.ResultsA reversible one-tissue compartment model was shown to best describe tracer uptake in breast cancer. No significant differences were seen in kinetic or static parameters for different tumour receptor subtypes or grades. Kinetic and static parameters showed a good correlation.Conclusions18F-fluciclovine has potential in the imaging of primary breast cancer, but kinetic analysis may not have additional value over static measures of tracer uptake.Clinical Trial RegistrationNCT03036943.

Implementing an X-ray tomography method for fusion devices

In fusion devices, the X-ray plasma emissivity contains essential information on the magnetohydrodynamic activity, the magnetic equilibrium and on the transport of impurities, in particular for tokamaks in the soft X-ray (SXR) energy range of 0.1–20 keV. In this context, tomography diagnostics are a key method to estimate the local plasma emissivity from a given set of line-integrated measurements. Unfortunately, the reconstruction problem is mathematically ill-posed, due to very sparse and noisy measurements, requiring an adequate regularization procedure. The goal of this paper is to introduce, with a didactic approach, some methodology and tools to develop an X-ray tomography algorithm. Based on a simple 1D tomography problem, the Tikhonov regularization is described in detail with a study of the optimal reconstruction parameters, such as the choice of the emissivity spatial resolution and the regularization parameter. A methodology is proposed to perform an in situ sensitivity and position cross-calibration of the detectors with an iterative procedure, by using the information redundancy and data variability in a given set of reconstructed profiles. Finally, the basic steps to build a synthetic tomography diagnostics in a more realistic tokamak environment are introduced, together with some tools to assess the capabilities of the 2D tomography algorithm.

Synthetic X-ray Tomography Diagnostics for Tokamak Plasmas

Tomography diagnostics represent an essential tool in tokamaks to infer the local plasma properties using line-integrated measurements from one or several cameras. In particular, soft X-rays (SXR) in the energy range 0.1–20 keV can provide valuable information on magnetohydrodynamic activity, magnetic equilibrium or impurity transport. Heavy impurities like tungsten (W) are a major source of concern due to significant radiation losses in the plasma core, thus they have to be kept under acceptable concentrations. Therefore, 2D SXR tomography diagnostics become crucial to estimate the W concentration profile in the plasma, quantify the W poloidal distribution and identify relevant impurity mitigation strategies. In this context, a synthetic diagnostic becomes a very valuable tool (1) to study the tomographic reconstruction capabilities, (2) to validate diagnostic design as well as (3) to assess the error propagation during the reconstruction process and impurity transport analysis. The goal of this contribution is to give some highlights on recent studies related to each of these three steps, for the development of SXR synthetic diagnostic tools in tokamak plasmas.

On the validity of the eikonal equation for surface-wave phase-velocity tomography

SUMMARYThe phase velocity of surface waves can be directly determined from the amplitude and phase of the regional wavefield using the Helmholtz equation. However, the Helmholtz equation involves estimating the Laplacian of the amplitude field, a challenging operation to perform on noisy and sparsely sampled seismic data. For this reason, the amplitude information is often discarded. In that case, phase-velocity maps are reconstructed with the eikonal equation, which relates the local phase slowness to the gradient of the phase. Here, we derive analytical expression of the errors arising from neglecting the amplitude of the wavefield in eikonal tomography. In general, these errors are quite strong but they vary sinusoidally with the wave propagation direction. Consequently, if the azimuthal coverage is good, they will average out, and unbiased phase-velocity maps can be obtained with eikonal tomography. We numerically validate these results with a synthetic tomography experiment.

Constraints on the presence of post-perovskite in Earth's lowermost mantle from tomographic-geodynamic model comparisons

Lower mantle tomography models consistently feature an increase in the ratio of shear-wave velocity (VS) to compressional-wave velocity (VP) variations and a negative correlation between shear-wave and bulk-sound velocity (VC) variations. These seismic characteristics, also observed in the recent SP12RTS model, have been interpreted to be indicative of large-scale chemical variations. Other explanations, such as the lower mantle post-perovskite (pPv) phase, which would not require chemical heterogeneity, have been explored less. Constraining the origin of these seismic features is important, as geodynamic simulations predict a fundamentally different style of mantle convection under both scenarios. Here, we investigate to what extent the presence of pPv explains the observed high VS/VP ratios and negative VS–VC correlation globally. We compare the statistical properties of SP12RTS with the statistics of synthetic tomography models, derived from both thermal and thermochemical models of 3-D global mantle convection. We convert the temperature fields of these models into seismic velocity structures using mineral physics lookup tables with and without pPv. We account for the limited tomographic resolution of SP12RTS using its resolution operator for both VS and VP structures. This allows for direct comparisons of the resulting velocity ratios and correlations. Although the tomographic filtering significantly affects the synthetic tomography images, we demonstrate that the effect of pPv remains evident in the ratios and correlations of seismic velocities. We find that lateral variations in the presence of pPv have a dominant influence on the VS/VP ratio and VS–VC correlation, which are thus unsuitable measures to constrain the presence of large-scale chemical variations in the lowermost mantle. To explain the decrease in the VS/VP ratio of SP12RTS close to the CMB, our results favour a pPv-bearing CMB region, which has implications for the stability field of pPv in the Earth's mantle.

Evaluating the Resolution of Deep Mantle Plumes in Teleseismic Traveltime Tomography

AbstractThe strongest evidence to support the classical plume hypothesis comes from seismic imaging of the mantle beneath hot spots. However, imaging results are often ambiguous and it is questionable whether narrow plume tails can be detected by present‐day seismological techniques. Here we carry out synthetic tomography experiments based on spectral element method simulations of seismic waves with period T > 10 s propagating through geodynamically derived plume structures. We vary the source‐receiver geometry in order to explore the conditions under which lower mantle plume tails may be detected seismically. We determine that wide‐aperture (4,000–6,000 km) networks with dense station coverage (<100–200 km station spacing) are necessary to image narrow (<500 km wide) thermal plume tails. We find that if uncertainties on traveltime measurements exceed delay times imparted by plume tails (typically <1 s), the plume tails are concealed in seismic images. Vertically propagating SKS waves enhance plume tail recovery but lack vertical resolution in regions that are not independently constrained by direct S paths. We demonstrate how vertical smearing of an upper mantle low‐velocity anomaly can appear as a plume originating in the deep mantle. Our results are useful for interpreting previous plume imaging experiments and guide the design of future experiments.

Comparison of slug and pumping tests for hydraulic tomography experiments: a practical perspective

Hydraulic tomography is the simultaneous analysis of several hydraulic tests performed in multiple isolated intervals in adjacent wells to image heterogeneous hydraulic property fields. In this study, we compare the resolutions associated with hydraulic tomography experiments carried out with slug tests and pumping tests for simple configurations with hydraulic property values representative of an extensively studied littoral aquifer. Associated test designs (e.g., pumping rates, test durations) and the validity of the principle of reciprocity are also assessed. For this purpose, synthetic tomography experiments and their associated sensitivity matrices are generated using a radial flow model accounting for wellbore storage. The resolution analysis is based on a pseudo-inverse analysis of the sensitivity matrix with a noise level representative of field measurements. Synthetic experiments used equivalent perturbations for slug tests and pumping tests. Even though pumping tests induce a drawdown in observation intervals that is three times larger than head changes due to slug tests, resolutions for hydraulic conductivities (horizontal and vertical) are similar for the two tests and slightly lower for specific storage with pumping. However, experiments with pumping require fifty times more water and are seven times longer to perform than experiments with slug tests. Furthermore, reducing pumping rates to limit disposal of water or test durations to decrease field data acquisition time would considerably lower resolutions for either scenario. Analyses are done using all available stressed and observation intervals as required by the non-applicability of the principle of reciprocity for slug tests and pumping tests with important wellbore storage. This study demonstrates concepts that have important implications for the performance and analysis of hydraulic tomography experiments.

Representing anisotropic subduction zones with isotropic velocity models: A characterization of the problem and some steps on a possible path forward

AbstractDespite the widely known fact that mantle flow in and around subduction zones produces the development of considerable seismic anisotropy, most P‐wave tomography efforts still rely on the assumption of isotropy. In this study, we explore the potential effects of erroneous assumption on tomographic images and explore an alternative approach. We conduct a series of synthetic tomography tests based on a geodynamic simulation of subduction and rollback. The simulation results provide a self‐consistent distribution of isotropic (thermal) anomalies and seismic anisotropy which we use to calculate synthetic delay times for a number of realistic and hypothetical event distributions. We find that anisotropy‐induced artifacts are abundant and significant for teleseismic, local and mixed event distributions. The occurrence of artifacts is not reduced, and indeed can be exacerbated, by increasing richness in ray‐path azimuths and incidence angles. The artifacts that we observe are, in all cases, important enough to significantly impact the interpretation of the images. We test an approach based on prescribing the anisotropy field as an a priori constraint and find that even coarse approximations to the true anisotropy field produce useful results. Using approximate anisotropy, fields can result in reduced RMS misfit to the travel time delays and reduced abundance and severity of imaging artifacts. We propose that the use of anisotropy fields derived from geodynamic modeling and constrained by seismic observables may constitute a viable alternative to isotropic tomography that does not require the inversion for anisotropy parameters in each node of the model.

MO-DE-209-01: Primer On Tomosynthesis

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis image acquisition. 2. To understand the fundamentals of tomosynthesis image reconstruction. 3. To learn the determinants of image quality and dose in DBT, including measurement techniques. 4. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care

MO-DE-209-02: Tomosynthesis Reconstruction Methods

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis image acquisition. 2. To understand the fundamentals of tomosynthesis image reconstruction. 3. To learn the determinants of image quality and dose in DBT, including measurement techniques. 4. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care

MO-DE-209-00: DBT Physics Basic to Advanced

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: 1.To understand the fundamental principles behind tomosynthesis image acquisition. 2.To understand the fundamentals of tomosynthesis image reconstruction. 3.To learn the determinants of image quality and dose in DBT, including measurement techniques. 4.To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care

MO-DE-209-03: Assessing Image Quality

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: 1.To understand the fundamental principles behind tomosynthesis image acquisition. 2.To understand the fundamentals of tomosynthesis image reconstruction. 3.To learn the determinants of image quality and dose in DBT, including measurement techniques. 4.To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care

MO-DE-209-04: Radiation Dosimetry in Breast Tomosynthesis

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis image acquisition. 2. To understand the fundamentals of tomosynthesis image reconstruction. 3. To learn the determinants of image quality and dose in DBT, including measurement techniques. 4. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care

TU-AB-207-01: Introduction to Tomosynthesis

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact, the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. 2. To learn how to test the performance of tomosynthesis imaging systems. 3. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.

TU-AB-207-03: Tomosynthesis: Clinical Applications

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact, the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. 2. To learn how to test the performance of tomosynthesis imaging systems. 3. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.

TU-AB-207-00: Digital Tomosynthesis

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact, the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. 2. To learn how to test the performance of tomosynthesis imaging systems. 3. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.

TU-AB-207-02: Testing of Body and Breast Tomosynthesis Sytems

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact, the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: 1. To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. 2. To learn how to test the performance of tomosynthesis imaging systems. 3. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.

CHROMOSPHERIC DIAGNOSIS WITH Ca II LINES: FORWARD MODELING IN FORWARD SCATTERING. I

This paper shows the first synthetic tomography of the quiet solar chromosphere formed by spatial maps of scattering polarization. It has been calculated for the CaII 8498, 8542 and 3934 A lines by solving the NLTE (non-local thermodynamical equilibrium) RT (radiative transfer) problem of the second kind in a 3D atmosphere model obtained from realistic MHD (magneto-hydrodynamical) simulations. Maps of circular polarization were calculated neglecting atomic polarization. Our investigation focuses on the linear polarization signals induced by kinematics, radiation field anisotropy and Hanle effect in forward-scattering geometry. Thus, instead of considering slit profiles at the limb as normally done in the study of the second solar spectrum, we synthetize and analyze spatial maps of polarization at disk center. It allows us to understand the spatial signatures of dynamics and magnetic field in the linear polarization for discriminating them observationally. Our results suggest new ideas for chromospheric diagnosis that will be developed throughout a serie of papers. In particular, Hanle Polarity Inversion Lines and dynamic Hanle diagrams are two concepts introduced in the present work. We find that chromospheric dynamics and magnetic field topology create spatial fingerprints in the polarization maps that trace the dynamic situation of the plasma and the magnetic field. Based on such spatial features we reconstruct the magnetic field intensity in the middle chromosphere along grooves of null linear polarization. We finally address the problems of diagnosing Hanle saturation and kinematic amplification of scattering signals using Hanle diagrams.