Joseph Reynolds

Next generation imager performance model

The next generation of Army imager performance models is currently under development at NVESD. The aim of this new model is to provide a flexible and extensible engineering tool for system design which encapsulates all of the capabilities of the existing Night Vision model suite (NVThermIP, SSCamIP, etc) along with many new design tools and features including a more intuitive interface, the ability to perform trade studies, and a library of standard and user generated components. By combining the previous model architectures in one interface the new design is better suited to capture emerging technologies such as fusion and new sensor modalities. In this paper we will describe the general structure of the model and some of its current capabilities along with future development plans.

A multi-source inverse-geometry CT system: initial results with an 8 spot x-ray source array

We present initial experimental results of a rotating-gantry multi-source inverse-geometry CT (MS-IGCT) system. The MS-IGCT system was built with a single module of 2 × 4 x-ray sources and a 2D detector array. It produced a 75 mm in-plane field-of-view (FOV) with 160 mm axial coverage in a single gantry rotation. To evaluate system performance, a 2.5 inch diameter uniform PMMA cylinder phantom, a 200 µm diameter tungsten wire, and a euthanized rat were scanned. Each scan acquired 125 views per source and the gantry rotation time was 1 s per revolution. Geometric calibration was performed using a bead phantom. The scanning parameters were 80 kVp, 125 mA, and 5.4 µs pulse per source location per view. A data normalization technique was applied to the acquired projection data, and beam hardening and spectral nonlinearities of each detector channel were corrected. For image reconstruction, the projection data of each source row were rebinned into a full cone beam data set, and the FDK algorithm was used. The reconstructed volumes from upper and lower source rows shared an overlap volume which was combined in image space. The images of the uniform PMMA cylinder phantom showed good uniformity and no apparent artifacts. The measured in-plane MTF showed 13 lp cm(-1) at 10% cutoff, in good agreement with expectations. The rat data were also reconstructed reliably. The initial experimental results from this rotating-gantry MS-IGCT system demonstrated its ability to image a complex anatomical object without any significant image artifacts and to achieve high image resolution and large axial coverage in a single gantry rotation.

Multi-source inverse-geometry CT: From system concept to research prototype

Third-generation CT architectures are approaching fundamental limits. Dose-efficiency is limited by finite detector efficiency and by limited control over the X-ray flux spatial profile. Increasing the volumetric coverage comes with increased scattered radiation, cone-beam artifacts, Heel effect, wasted dose and cost. Spatial resolution is limited by focal spot size and detector cell size. Temporal resolution is limited by mechanical constraints, and alternative geometries such as electron-beam CT and dual-source CT come with severe tradeoffs in terms of image quality, dose-efficiency and complexity. The concept of multi-source inverse-geometry CT (IGCT) breaks through several of the above limitations [1-3], promising a low-dose high image quality volumetric CT architecture. In this paper, we present recent progress with the design and integration efforts of the first gantry-based multi-source CT scanner.

IR system field performance with superresolution

Superresolution processing is currently being used to improve the performance of infrared imagers through an increase in sampling, the removal of aliasing, and the reduction of fixed-pattern noise. The performance improvement of superresolution has not been previously tested on military targets. This paper presents the results of human perception experiments to determine field performance on the NVESD standard military eight (8)-target set using a prototype LWIR camera. These experiments test and compare human performance of both still images and movie clips, each generated with and without superresolution processing. Lockheed Martins XR® algorithm is tested as a specific example of a modern combined superresolution and image processing algorithm. Basic superresolution with no additional processing is tested to help determine the benefit of separate processes. The superresolution processing is modeled in NVThermIP for comparison to the perception test. The measured range to 70% probability of identification using XR® is increased by approximately 34% while the 50% range is increased by approximately 19% for this camera. A comparison case is modeled using a more undersampled commercial MWIR sensor that predicts a 45% increase in range performance from superresolution.

Multisource inverse-geometry CT — Prototype system integration

Todays 3rd generation CT scanners have one or two X-ray tubes, with one focal spot or “source” per vacuum chamber or “tube”. Our first multi-source inverse geometry CT prototype has eight X-ray sources. We have demonstrated multisource imaging with an 8-spot X-ray tube on a stationary gantry and a rotating phantom. We present an update on the development of the gantry-based multi-source CT scanner: we combine the multi-source X-ray tube and gantry rotation producing the first multi-source gantry-based CT scanner prototype. Currently the system is in the process of being upgraded to 32 X-ray sources to provide a larger field-of-view and to demonstrate the concept of virtual bowtie.

Initial results with a multisource inverse-geometry CT system

The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. An experimental MS-IGCT system was built and we report initial results with 2×4 x-ray sources, a 75 mm inplane field-of-view (FOV) and 160 mm z-coverage in a single gantry rotation. To evaluate the system performance, experimental data were acquired from several phantoms and a post-mortem rat. Before image reconstruction, geometric calibration, data normalization, beam hardening correction and detector spectral calibration were performed. For reconstruction, the projection data were rebinned into two full cone beam data sets, and the FDK algorithm was used. The reconstructed volumes from the upper and lower source rows shared an overlap volume which was combined in image space. The reconstructed images of the uniform cylinder phantom showed good uniformity of the reconstructed values without any artifacts. The rat data were also reconstructed reliably. The initial experimental results from this rotating-gantry MS-IGCT system demonstrated its ability to image a complex anatomical object without any significant image artifacts and to ultimately achieve large volumetric coverage in a single gantry rotation.

Comparison of perception results with a proposed model for detection of a stationary target from a moving platform

A model has been developed that predicts the probability of detection as a function of time for a sensor on a moving platform looking for a stationary object. The proposed model takes as input P (calculated from NVThermIP), expresses it as a function of time using the known sensor-target range and outputs detection probability as a function of time. The proposed search model has one calibration factor that is determined from the mean time to detect the target. Simulated imagery was generated that models a vehicle moving with constant speed along a straight road with varied vegetation on both sides and occasional debris on the road and on the shoulder. Alongside, and occasionally on the road, triangular and square shapes are visible with a contrast similar to that of the background but with a different texture. These serve as targets to be detected. In perception tests, the ability of observers to detect the simulated targets was measured and excellent agreement was observed between modeled and measured results.

Optimization of display viewing distance for human observers in the noise-limited case

In the pursuit of fully-automated display optimization, the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) is evaluating a variety of approaches, including the effects of viewing distance and magnification on target acquisition performance. Two such approaches are the Targeting Task Performance (TTP) metric, which NVESD has developed to model target acquisition performance in a wide range of conditions, and a newer Detectivity metric, based on matched-filter analysis by the observer. While NVESD has previously evaluated the TTP metric for predicting the peak-performance viewing distance as a function of blur, no such study has been done for noise-limited conditions. In this paper, the authors present a study of human task performance for images with noise versus viewing distance using both metrics. Experimental results are compared to predictions using the Night Vision Integrated Performance Model (NV-IPM). The potential impact of the results on the development of automated display optimization are discussed, as well as assumptions that must be made about the targets being displayed.

Analytical calculation for probability of detection given time-dependent search parameters

The problem solved in this paper is easily stated: given search parameters (p∞, τ) that are known functions of time, calculate how the probability a single observer acquires a target grows with time. This problem has been solved analytically. In this paper we describe the analytical solution and provide derivations of the results. Comparison with perception experiments will be reported in a future publication and hopefully will support the results presented here. The provided solution is applicable to any scenario where the search parameters are changing with time and are specified. In particular, the solution can be used to estimate the probability of target acquisition as a function of time: (1) when the sensor-target range is changing, (2) for a slewed sensor where the target is alternately in and out of the field of view, and (3) for a sensor that switches between wide and narrow fields of view.

Collaborative search with independent sensors and multiple observers

In this paper we address these problems. 1) Two stationary observers with two sensors independently search for a stationary target. Each sensor is characterized by individual search parameters (p∞, τ) which are different either because the sensors are at different ranges or are different because the sensors are at the same range but have different properties. The target is said to be detected when the first observer detects the target. Using this definition for time to detect, we derive an analytical expression for the mean detection time. 2) If multiple observers independently search an image obtained from a single sensor how does the mean time until the first observer detects the target vary with the number of observers. 3) If multiple observers independently search an image obtained from a single sensor how does the probability of detection vary with the number of observers. Here the target is said to be detected if any of the observers detect the target. 4) For the problem of two stationary observers searching independently for a stationary target we found the probability density function for the time to detect.