Source localization for neutron imaging systems using convolutional neural networks.

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for determining the geometry of inertial confinement fusion implosions. The geometry is reconstructed from a neutron aperture image via a set of reconstruction algorithms using an iterative Bayesian inference approach. An important step in these reconstruction algorithms is finding the fusion source location within the camera field-of-view. Currently, source localization is achieved via an iterative optimization algorithm. In this paper, we introduce a machine learning approach for source localization. Specifically, we train a convolutional neural network to predict source locations given a neutron aperture image. We show that this approach decreases computation time by several orders of magnitude compared to the current optimization-based source localization while achieving similar accuracy on both synthetic data and a collection of recent NIF deuterium-tritium shots.

Bootstrap estimation of the effect of instrument response function uncertainty on the reconstruction of fusion neutron sources.

Neutron imagers are important diagnostics for the inertial confinement fusion implosions at the National Ignition Facility. They provide two- and three-dimensional reconstructions of the neutron source shape that are key indicators of the overall performance. To interpret the shape results properly, it is critical to estimate the uncertainty in those reconstructions. There are two main sources of uncertainties: limited neutron statistics, leading to random errors in the reconstructed images, and incomplete knowledge of the instrument response function (the pinhole-dependent point spread function). While the statistical errors dominate the uncertainty for lower yield deuterium-tritium (DT) shots, errors due to the instrument response function dominate the uncertainty for DT yields on the order of 1016 neutrons or higher. In this work, a bootstrapping method estimates the uncertainty in a reconstructed image due to the incomplete knowledge of the instrument response function. The main reconstruction is created from the fixed collection of pinhole images that are best aligned with the neutron source. Additional reconstructions are then built using subsets of that collection of images. Variations in the shapes of these additional reconstructions originate solely from uncertainties in the instrument response function, allowing us to use them to provide an additional systematic uncertainty estimate.

Contrast-enhanced proton radiographic sensitivity limits for tumor detection.

Purpose: Proton radiography may guide proton therapy cancer treatments with beam's-eye-view anatomical images and a proton-based estimation of proton stopping power. However, without contrast enhancement, proton radiography will not be able to distinguish tumor from tissue. To provide this contrast, functionalized, high- Z nanoparticles that specifically target a tumor could be injected into a patient before imaging. We conducted this study to understand the ability of gold, as a high- Z , biologically compatible tracer, to differentiate tumors from surrounding tissue. Approach: Acrylic and gold phantoms simulate a tumor tagged with gold nanoparticles (AuNPs). Calculations correlate a given thickness of gold to levels of tumor AuNP uptake reported in the literature. An identity, × 3 , and × 7 proton magnifying lens acquired lens-refocused proton radiographs at the 800-MeV LANSCE proton beam. The effects of gold in the phantoms, in terms of percent density change, were observed as changes in measured transmission. Variable areal densities of acrylic modeled the thickness of the human body. Results: A 1 - µ m -thick gold strip was discernible within 1 cm of acrylic, an areal density change of 0.2%. Behind 20 cm of acrylic, a 40 - µ m gold strip was visible. A 1-cm-diameter tumor tagged with 1 × 10 5 50-nm AuNPs per cell has an amount of contrast agent embedded within it that is equivalent to a 65 - µ m thickness of gold, an areal density change of 0.63% in a tissue thickness of 20 cm, which is expected to be visible in a typical proton radiograph. Conclusions: We indicate that AuNP-enhanced proton radiography might be a feasible technology to provide image-guidance to proton therapy, potentially reducing off-target effects and sparing nearby tissue. These data can be used to develop treatment plans and clinical applications can be derived from the simulations.

A liquid VI scintillator cell for fast-gated neutron imaging.

The design of a new fast-gated neutron imaging system for the National Ignition Facility with much stricter timing constraints than a previous system has prompted the search for a fast scintillator material that can be used in imaging. A novel imaging cell based on Liquid VI has recently been developed with Eljen Technology and characterized at the Special Technologies Laboratory and the Los Alamos Neutron Science Center. The results show superior timing characteristics and spatial resolution, and sufficient light production for the new system compared to fast plastic scintillators previously used in neutron imaging. While the primary application is in inertial confinement fusion diagnostics, the imaging cell can be used in any fast-gated imaging application where timing characteristics and spatial resolution are of concern.

Inverse-collimated proton radiography for imaging thin materials.

Relativistic, magnetically focused proton radiography was invented at Los Alamos National Laboratory using the 800 MeV LANSCE beam and is inherently well-suited to imaging dense objects, at areal densities >20 g cm-2. However, if the unscattered portion of the transmitted beam is removed at the Fourier plane through inverse-collimation, this system becomes highly sensitive to very thin media, of areal densities <100 mg cm-2. Here, this inverse-collimation scheme is described in detail and demonstrated by imaging Xe gas with a shockwave generated by an aluminum plate compressing the gas at Mach 8.8. With a 5-mrad inverse collimator, an areal density change of just 49 mg cm-2 across the shock front is discernible with a contrast-to-noise ratio of 3. Geant4 modeling of idealized and realistic proton transports can guide the design of inverse-collimators optimized for specific experimental conditions and show that this technique performs better for thin targets with reduced incident proton beam emittance. This work increases the range of areal densities to which the system is sensitive to span from ∼25 mg cm-2 to 100 g cm-2, exceeding three orders of magnitude. This enables the simultaneous imaging of a dense system as well as thin jets and ejecta material that are otherwise difficult to characterize with high-energy proton radiography.

The National Ignition Facility neutron imaging system.

The National Ignition Facility (NIF) is scheduled to begin deuterium-tritium (DT) shots possibly in the next several years. One of the important diagnostics in understanding capsule behavior and to guide changes in Hohlraum illumination, capsule design, and geometry will be neutron imaging of both the primary 14 MeV neutrons and the lower-energy downscattered neutrons in the 6-13 MeV range. The neutron imaging system (NIS) described here, which we are currently building for use on NIF, uses a precisely aligned set of apertures near the target to form the neutron images on a segmented scintillator. The images are recorded on a gated, intensified charge coupled device. Although the aperture set may be as close as 20 cm to the target, the imaging camera system will be located at a distance of 28 m from the target. At 28 m the camera system is outside the NIF building. Because of the distance and shielding, the imager will be able to obtain images with little background noise. The imager will be capable of imaging downscattered neutrons from failed capsules with yields Y(n)>10(14) neutrons. The shielding will also permit the NIS to function at neutron yields >10(18), which is in contrast to most other diagnostics that may not work at high neutron yields. The following describes the current NIF NIS design and compares the predicted performance with the NIF specifications that must be satisfied to generate images that can be interpreted to understand results of a particular shot. The current design, including the aperture, scintillator, camera system, and reconstruction methods, is briefly described. System modeling of the existing Omega NIS and comparison with the Omega data that guided the NIF design based on our Omega results is described. We will show NIS model calculations of the expected NIF images based on component evaluations at Omega. We will also compare the calculated NIF input images with those unfolded from the NIS images generated from our NIS numerical modeling code.