Multi-energy, Limited View Computed Tomography (CT)
Overview and Significance
The development of energy selective photon counting detectors for X-ray sensing applications has created the possibility for significantly enhancing materials characterization capabilities relative to existing energy integrating or dual-energy systems. Energy integrating methods provide information only regarding material
density while dual energy systems, at best, can image both density and effective atomic number (or equivalently spatial maps of Compton and photoelectric coefficients). In practice, the overlapping nature of the spectra employed in fielded dual energy systems as well as the nature of X-ray physics, significantly complicates the stable recovery of atomic number. As we argue in this report, multi- or hyper-spectral forms of sensing, where data are collected over a large number of narrow energy bins in such a manner as to reflect both attenuation as well as X-ray scattering, have the potential to move X-ray based screening significantly beyond the limitations of the current state-of-the-art systems. In a bit more detail, the energy integrating and dual-energy methods recover information concerning the object of interest based on the manner in which X-rays are attenuated as they pass through the medium. The attenuation properties in turn reflect both the absorption of the X-rays as well as the scattering of the X-ray photons from the beam. For all fielded X-ray systems in use by DHS, these scattered photons are ignored. It is our hypothesis that there is significant information embedded in these photons such that their collection and processing can enhance the ability of DHS to characterize materials from X-ray data specifically in the context of limited view systems currently under investigation and development. Indeed, in recent years, DHS has been exploring X-ray systems comprised of spatially fixed sources and detectors in contrast to traditional computed tomography (CT) types of systems where source/detector arrays rotate around the items being scanned. Complicating the development of these systems, the limited number of source-detector paths compared to the full-scale CT case creates substantial challenges in terms of image formation and, ultimately, target detection. As we demonstrate in this report, using the detectors in these systems to collect scattered photons (in addition to the traditional attenuation-based data) significantly increases the number of “looks” we have at the scene even in these fixed geometries potentially allowing us to greatly enhance the information content provided by these systems.
In this regard, the most interesting scattering process for the energy range of interest in this application domain, Compton scattering, is characterized by two key properties. First, the intensity of Compton scattering is directly proportional to the electron density in the vicinity of the event. Second, Compton scattering is inelastic, meaning that the energy of the photons shift after a scattering event, thereby necessitating the use of energy resolving detectors to usefully capture and quantify these processes. The shift in energy determines the direction in which photons are scattered. In a sense that we make more precise shortly, this energy-dependent scattering direction very much “encodes” electron density at a specific location. These two properties have significant systems-level implications for DHS.
Realizing this potential, however, requires that we address a number of challenges. First, the physical processes and mathematical/computational models associated with these scattering processes are more complex than traditional attenuation imaging. The development of a model, which links the observed data to the material properties of interest, is necessary to address the second challenge: how we use these scattered photons in addition to traditional attenuation data to form images. Only after these image formation methods are in place can we quantify the true benefits of these new data; e.g., attainable image resolution and reduction in imaging artifacts, as well as target detection and false alarm rates. Over the past year, we have focused on the first of these challenges: model development. By building on related efforts in Compton and Fluorescence X-ray imaging, we have constructed a mathematical model relating the scattered photon data to the spatial distributions of material properties that we will seek to image, specifically the photoelectric absorption coefficient and mass density, which is proportional to electron density. In this time period, we have developed a computational code for this model using the Matlab programming environment. The code has been designed specifically to be efficient when used as part of an image formation algorithm, which will take observed data and produce estimates of photoelectric coefficients and density. Developing these algorithms and using them to quantify the value of this new and interesting data type constitute the work on this project for the remaining two years.
The significance of this project relative to the larger ALERT program lies in the potential of these models and associated processing methods to improve the accuracy of screening both checked baggage as well as luggage inspected at the checkpoint. The algorithms at the heart of the current collection of TSA certified systems are not sufficient for the processing of the data that will be produced by the next generation of X-ray scanning systems. Even the state-of-the-art model based iterative reconstruction methods are not designed to fully exploit the information provided by multi-/hyper-spectral X-ray data. Neither are they capable of addressing the challenges encountered when considering the severely limited view nature of the data provided by these fixed source/fixed detector systems. Our proposed approach to explore the utility of scattered X-ray information to materials characterization is intended to address both of these challenges and, to the best of our knowledge, is the only effort within the ALERT program with this focus.
Finally, we note the steps taken by this team in the area of technology transition. In addition to regular attendance and presentation of this work at the Advanced Development for Security Applications (ADSA) meetings held over the past seven years, Professors Miller and Tracey are partnering with American Science and Engineering (AS&E) and Lawrence Livermore National Laboratory (LLNL) on a soon-to-be awarded project under the 13-05 DHS RFP devoted to the development of next generation X-ray scanning systems. As part of this collaboration, AS&E has committed to collecting data on the system they will be developing and that will be employed specifically to validate the models and processing methods being developed as part of this project.
By building on related efforts in Compton and Fluorescence X-ray imaging, we have constructed a mathematical model relating the scattered photon data to the spatial distributions of material properties that we will seek to image, specifically the photoelectric absorption coefficient and mass density, which is proportional to electron density.Phase 2 Year 2 Annual Report
Faculty and Staff Currently Involved in Project
Research Assistant Professor
Students Currently Involved in Project
- Hamideh Rezaee
- Jon Foley