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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AAPM Truth‐based CT (TrueCT) reconstruction grand challenge

Background: This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction. Purpose: To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases. Methods: Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions. The organs were modeled based on clinical CT images of real patients. The emphysematous regions were modeled using segmentations from patient CT cases in the COPDGene Phase I dataset. For the lung and liver lesion cases, 1–6 malignant lesions were created and inserted into the human models, with lesion diameters ranging from 5.6 to 21.9 mm for lung lesions and 3.9 to 14.9 mm for liver lesions. The contrast defined between the liver lesions and liver parenchyma was 82 ± 12 HU, ranging from 50 to 110 HU. Similarly, the contrast between the lung lesions and the lung parenchyma was defined as 781 ± 11 HU, ranging from 725 to 805 HU. For the emphysematous regions, the defined HU values were −950 ± 17 HU ranging from −918 to −979 HU. The developed human models were imaged with a validated CT simulator. The resulting CT sinograms were shared with the participants. The participants reconstructed CT images from the sinograms and sent back their reconstructed images. Further, the reconstructed images were then scored by comparing the results against the corresponding ground truth values. The scores included both task-generic (root mean square error [RMSE] and structural similarity matrix [SSIM]), and task-specific (detectability index [d’] and lesion volume accuracy) metrics. For the cases with multiple lesions, the measured metric was averaged across all the lesions. To combine the metrics with each other, each metric was normalized to a range of 0 to 1 per disease type, with “0” and “1” being the worst and best measured values across all cases of the disease type for all received reconstructions. Results: The True-CT challenge attracted 52 participants, out of which 5 successfully completed the challenge and submitted the requested 200 reconstructions. Across all participants and disease types, SSIM absolute values ranged from 0.22 to 0.90, RMSE from 77.6 to 490.5 HU, d’ from 0.1 to 64.6, and volume accuracy ranged from 1.2 to 753.1 mm3. The overall scores demonstrated that participant “A” had the best performance in all categories, except for the metrics of d’ for lung lesions and RMSE for liver lesions. Participant “A” had an average normalized score of 0.41 ± 0.22, 0.48 ± 0.32, and 0.42 ± 0.33 for the emphysema, lung lesion, and liver lesion cases, respectively. Conclusions: The True-CT challenge successfully enabled objective assessment of CT reconstructions with the unique advantage of access to a diverse population of diseased human models with known ground truth. This study highlights the significant potential of virtual imaging trials in objective assessment of medical imaging technologies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1996

Application of Linear Array Imaging Techniques to the Real-Time Inspection of Airframe Structures and Substructures

Current concern for ensuring, the air-worthiness of the aging commercial air fleet has prompted the establishment of broad-agency programs to develop NDT technologies that address specific aging-aircraft issues. One of the crucial technological needs that has been identified is the development of rapid, quantitative systems for depot-level inspection of bonded aluminum lap joints on aircraft. Research results for characterization of disbond and corrosion based on normal-incidence pulse-echo measurement geometries are showing promise, but are limited by the single-site nature of the measurement which requires manual or mechanical scanning to inspect an area. One approach to developing efficient systems may be to transfer specific aspects of current medical imaging technology to the NDT arena. Ultrasonic medical imaging, systems offer many desirable attributes for large scale inspection. They are portable, provide real-time imaging, and have integrated video tape recorder and printer capabilities available for documentation and post-inspection review. Furthermore, these systems are available at a relatively low cost (approximately $50,000 to $200,000) and can be optimized for use with metals with straight-forward modifications.

Miller, James G.↗
DOE OSTI2026

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cutaneous and local radiation injuries

The threat of a large-scale radiological or nuclear (R/N) incident looms in the present-day climate, as noted most recently in an editorial in Scientific American (March 2021). These large-scale incidents are infrequent but affect large numbers of people. Smaller-scale R/N incidents occur more often, affecting smaller numbers of people. There is more awareness of acute radiation syndrome (ARS) in the medical community; however, ionising radiation-induced injuries to the skin are much less understood. Here, this article will provide an overview of radiation-induced injuries to the skin, deeper tissues, and organs. The history and nomenclature; types and causes of injuries; pathophysiology; evaluation and diagnosis; current medical management; and current research of the evaluation and management are presented. Cutaneous radiation injuries (CRI) or local radiation injuries (LRI) may lead to cutaneous radiation syndrome, a sub-syndrome of ARS. These injuries may occur from exposure to radioactive particles suspended in the environment (air, soil, water) after a nuclear detonation or an improvised nuclear detonation (IND), a nuclear power plant incident, or an encounter with a radioactive dispersal or exposure device. These incidents may also result in a radiation-combined injury; a chemical, thermal, or traumatic injury, with radiation exposure. Skin injuries from medical diagnostic and therapeutic imaging, medical misadministration of nuclear medicine or radiotherapy, occupational exposures (including research) to radioactive sources are more common but are not the focus of this manuscript. Diagnosis and evaluation of injuries are based on the scenario, clinical picture, and dosimetry, and may be assisted through advanced imaging techniques. Research-based multidisciplinary therapies, both in the laboratory and clinical trial environments, hold promise for future medical management. Great progress is being made in recognising the extent of injuries, understanding their pathophysiology, as well as diagnosis and management; however, research gaps still exist.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1996

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Knasel, T. Michael↗
DOE OSTI2025

Simultaneous on-chip generation of violet, blue, cyan, green, yellow, orange, and red light from an octave-spanning infrared frequency comb

An integrated, multi-spectral visible-light source could significantly benefit technologies such as displays, medical imaging, spectroscopy, visible-light communications, and astrophysics. However, despite recent advances in chip-scale visible lasers, simultaneously generating light of all colors in a single chip has been challenging. Existing solutions are either not suitable for full chip-scale integration, or are fundamentally difficult to scale. Here we demonstrate the simultaneous on-chip generation of infrared, red, orange, yellow, green, cyan, blue, and violet light. Leveraging the low loss, low dispersion, and high density of modes of an adiabatic multimode silicon nitride (SiN) microresonator, we use a single infrared pump of moderate power (~130 mW) to produce an octave-spanning infrared frequency comb that is then converted to different portions of the visible spectrum. We measure non-mode-locked combs and soliton steps corresponding to mode-locked states, making our comb generator suitable for applications that demand either low or high coherence. Since the required pump power is compatible with high-power lasers demonstrated in the same SiN platform, our multi-octave light generator can be fully integrated in a chip-scale form factor. We envision that such a light source will be a catalyst for the development and deployment of miniaturized multi-spectral technologies for quantum systems, medical imaging, displays, and spectroscopy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Performance of Scintillation Detectors Based on Quantum Dots in a Semiconductor Matrix (Final Technical Report)

InAs Quantum Dots (QDs) embedded into GaAs semiconductor waveguide have unique scintillation properties, valuable for nuclear security, medical imaging, and high energy physics. In this work, we developed thick (~25um) epitaxial heterostructres with high luminescence efficiency composed of self-assembled nano-engineered InAs QDs grown by molecular beam epitaxy. In this type of detector, the GaAs matrix acts as a stopping material for charged particles or photons generating electrons captured by the QDs acting as luminescence centers. The QD medium is designed to provide fast capture of electrons into QDs (few ps), high QD luminescence efficiency at room temperature (>50%), and strong red-shift of photoluminescence (PL) from the GaAs absorption edge (>250nm). Typical devices consist of a 10-25um thick GaAs layer with embedded sheets of modulation p-type doped InAs QDs and an InGaAs photodetector tuned to the QD emission wavelength. The thick GaAs layer acts also as a waveguide when layer-transferred onto a low-index substrate. Waveguiding and self-absorption (~1cm -1 ) were studied using photoluminescence with scanning laser excitation and modeled with ray optics approximation and geometrical coupling of high-index waveguide to a collection fiber. Scintillating signals from α-particles were analyzed with both an external photodiode (PD) and an integrated PD which provided an improved optical coupling. In the former case, the external InGaAs PD was air-coupled to the scintillator and had the light collection efficiency of about 1% corresponding to limited light extraction through a planar interface with air due to total internal reflection. The mean charge collected by the integrated PD was in the range of (3÷5)×10 4 photoelectrons per 1 MeV of deposited energy, or ~13-20% of the theoretically achievable light yield. Timing of the integrated device was measured by wire-bonding it to the input of an 8 GHz IC. The scintillation response shows an extremely fast 0.3-0.6 ns decay constant and about 40-70 ps time resolution, limited by the system noise. The combined light yield and decay time makes the InAs/GaAs QD heterostructures the fastest high yield scintillation material reported making it valuable for high energy physics and medical imaging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Adsorption separation of heavier isotope gases in subnanometer carbon pores

Isotopes of heavier gases including carbon ( 13 C/ 14 C), nitrogen ( 13 N), and oxygen ( 18 O) are highly important because they can be substituted for naturally occurring atoms without significantly perturbing the biochemical properties of the radiolabelled parent molecules. These labelled molecules are employed in clinical radiopharmaceuticals, in studies of brain disease and as imaging probes for advanced medical imaging techniques such as positron-emission tomography (PET). Established distillation-based isotope gas separation methods have a separation factor ( S ) below 1.05 and incur very high operating costs due to high energy consumption and long processing times, highlighting the need for new separation technologies. Here, we show a rapid and highly selective adsorption-based separation of 18 O 2 from 16 O 2 with S above 60 using nanoporous adsorbents operating near the boiling point of methane (112 K), which is accessible through cryogenic liquefied-natural-gas technology. A collective-nuclear-quantum effect difference between the ordered 18 O 2 and 16 O 2 molecular assemblies confined in subnanometer pores can explain the observed equilibrium separation and is applicable to other isotopic gases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determined by a leave one subject out (LOSO) holdout methodology. Introduction of affine transformations for image augmentation or MixUp methodologies to generate additional training sets improved model performance and overall accuracy improved to 75%. Further improvements were made by aggregating predictions across five LOSO holdouts. This was done by bagging confidences or predictions from all LOSOs or the top-3 LOSO confidence models for each image prediction. Top-3 LOSO confidence bagging performed best, with test accuracy improved to greater than 85% accuracy for two different blind tissue phantoms. This was confirmed by gradient-weighted class activation mapping to highlight that the image classifier was tracking shrapnel in the image sets. Overall, data augmentation and ensemble prediction approaches were suitable for creating more generalized predictive models for ultrasound image analysis, a critical step for real-time diagnostic deployment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Resistive Coatings for High-performance, Low-background MCPs Operating Across Broad Temperature Ranges and at Cryogenic Temperatures

Microchannel plate with improved thermo-electric properties are a high risk, high payoff development undertaken by a consortium of effort that links the Argonne National Lab, the Space-Science Lab at UC Berkeley and the small businesses (Incom Inc.) that will commercialize the advanced technology in open MCPs and LAPPDs. This development will satisfy the needs for new instrumentation for homeland security (non-proliferation) sensors to screen vehicles and cargo for Special Nuclear Materials (SNMs) and scientific detectors for astrophysics, electron microscopy, time-of-flight mass spectrometry, molecular and atomic collision studies, and fluorescence imaging applications in biotechnology and medical imaging products including positron emission tomography (PET scanning).

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Automated Registration of Multi-Mode Nondestructive Evaluation Data

Registration techniques play a central role in applications of image processing to computer vision, medical imaging, and automatic target tracking. Feature-based techniques such as scale-invariant feature transform (SIFT) and speeded up robust features (SURF) are commonly used to register images derived from a single modality. However, SIFT and SURF struggle to register images from different modalities because the features tend to manifest rather differently and at sometimes very different length-scales. The most successful methods that have been developed to register multi-modal data use information-theoretic approaches. These methods play a key part in nondestructive evaluation scenarios where data that is collected by sensors of different modalities must be registered to be fused. In this paper, automated registration based on normalized mutual information is applied to align data derived from ultrasonic and radiographic inspections of (i) additively manufactured titanium alloy test coupons, and (ii) thin, lithium metal pouch-cell batteries. The quality of the registration is quantified in terms of computational resources and spatial accuracy. In the first case the X-ray computed tomography (XCT) data is captured on a region corresponding to a small subset of the ultrasonic data, while in the case of the lithium batteries the digital radiography (DR) captures a larger region of interest than the ultrasonic data. In both cases the radiographic data resolution is much higher than for ultrasound, but interestingly, in both cases the accuracy of the registration is approximately equal to two-to-three-pixel lengths in the ultrasonic images.

Nondestructive Evaluation↗
NASA NTRS1978

Autoradiographic image intensification - Applications in medical radiography

The image of an 80 to 90 percent underexposed medical radiograph can be increased to readable density and contrast by autoradiographic image intensification. The technique consists of combining the image silver of the radiograph with a radioactive compound, thiourea labeled with sulfur-35, and then making an autoradiograph from the activated negative.

Askins, B. S.↗
DOE OSTI2022

Activator-doped Hg 2 Br 2 as next generation high performance scintillator for high energy physics research and other scientific and imaging applications

Existing COTS inorganic scintillators all have the characteristic of being very good at certain desirable properties, but not sufficient at other desirable properties for HEP. The demand for suitable scintillators (with regards to both scintillation detector properties and suitable pricing), to be used for modern intensities frontier (Mu2e-II), energy frontier (High luminosity large hadron collider) and future e+e- collider projects (aimed as Higgs bosons factory, such as the International Linear Collider (ILC) and the Future Circular Collider (FCC) are putting even higher challenges on crystal scintillators.In this work, we report the development of a novel high-performance scintillators that can address the issues associated with existing scintillators, the activator doped Hg2Br2. Initial results are very encouraging on the detection of gamma and alpha particles using a solid-state photomultiplier (SSPM). The responses have been stable and repeatable. Hg2Br2 also has many advantages over existing COTS scintillators such as: high density, bright, fast, good energy resolution, no intrinsic radiation, radiation hard and cost-effectiveness. Here, we present here why Hg2Br2 is the next generation scintillator for high energy physics experiments as well as other scientific and imaging applications such as planetary science and medical imaging.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Earth Resources Laboratory Applications Software (ELAS)

ELAS modified to handle broad range of digital images, and now finding widespread application in medical imaging field. Many versions of ELAS condensed into v. 8.0, which is available for DEC VAX, CONCURRENT, and for UNIX environment.

Penton, P. G.↗
NASA NTRS2011

Multi-Modal Image Registration and Matching for Localization of a Balloon on Titan

A solution was developed that matches visible/IR imagery aboard a balloon in Saturn's moon Titan's atmosphere to SAR (synthetic aperture radar) and visible/IR data acquired from orbit. A balloon in Titan's atmosphere must be able to localize itself autonomously both globally and with respect to local terrain. The orbital data is used to provide the balloon imagery with global context. The work is novel in applying mutual information (MI) to orbital vs. aerial data. There are unique challenges in this setting. Image offsets are much higher than in medical imaging, there is local distortion due to 3D terrain relief, and the fields of regard from orbit and from the air are quite different.

Ansar, Adnan I.↗
NASA NTRS2005

GaAs QWIP Array Containing More Than a Million Pixels

A 1,024 x 1,024-pixel array of quantum-well infrared photodetectors (QWIPs) has been built on a 1.8 x 1.8- cm GaAs chip. In tests, the array was found to perform well in detecting images at wavelengths from 8 to 9 m in operation at temperatures between 60 and 70 K. The largest-format QWIP prior array that performed successfully in tests contained 512 x 640 pixels. There is continuing development effort directed toward satisfying actual and anticipated demands to increase numbers of pixels and pixel sizes in order to increase the imaging resolution of infrared photodetector arrays. A 1,024 x 1,024-pixel and even larger formats have been achieved in the InSb and HgCdTe material systems, but photodetector arrays in these material systems are very expensive and manufactured by fewer than half a dozen large companies. In contrast, GaAs-photodetector-array technology is very mature, and photodetectors in the GaAs material system can be readily manufactured by a wide range of industrial technologists, by universities, and government laboratories. There is much similarity between processing in the GaAs industry and processing in the pervasive silicon industry. With respect to yield and cost, the performance of GaAs technology substantially exceeds that of InSb and HgCdTe technologies. In addition, GaAs detectors can be designed to respond to any portion of the wavelength range from 3 to about 16 micrometers - a feature that is very desirable for infrared imaging. GaAs QWIP arrays, like the present one, have potential for use as imaging sensors in infrared measuring instruments, infrared medical imaging systems, and infrared cameras.

Jhabvala, Murzy↗
DOE OSTI2025

An Overview of Emerging Nuclear Sensor Technologies: Challenges, Advancements and Applications

Nuclear sensors are essential for detecting and measuring nuclear radiation in various applications, including nuclear power plants, medical imaging, and environmental monitoring. Traditional nuclear sensors have served these fields for decades, but recent advancements in emerging sensor technologies offer novel improvements in accuracy, sensitivity, and reliability. This review presents an up-to-date overview of recent progress in the advancements of nuclear sensor technologies, their diverse applications, challenges in implementation, and opportunities for future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Metal Halide Scintillators with Fast and Self‐Absorption‐Free Defect‐Bound Excitonic Radioluminescence for Dynamic X‐Ray Imaging

Abstract Scintillators for radiation detection are of great significance in medical imaging, security, and nondestructive inspection. The current challenge for scintillators is to simultaneously achieve high scintillation light yield, fast radioluminescence, simple film fabrication, large X‐ray attenuation efficiency as well as stable and nontoxic compositions; no previous scintillators fulfill all the above requirements. Here, metal halide Rb 2 AgBr 3 , possessing defect‐bound excitonic radioluminescence, is shown as efficient and fast scintillators. This nontoxic and stable scintillator emits from excitons bound to neutral bromine vacancies, enjoying an efficient and spin‐allowed fast emission with minimized self‐absorption. Rb 2 AgBr 3 thus has a high light yield (25 600 photons MeV −1 ), fast scintillation decay time (5.31 ns), and a record value of light yield versus decay time (4821 photons MeV −1 ns −1 ). The close‐space sublimation method is developed for fast and scalable fabrication of oriented Rb 2 AgBr 3 films. The scintillator film is further integrated with commercial flat‐panel imagers, and the spatial resolution reaches 10.2 line pairs per millimeter at the modulation transfer function of 0.2, doubling the resolution of conventional CsI:Tl flat‐panel detectors. The dynamic X‐ray imaging and its use to real‐time monitoring of bone movement without ghosting effect is also demonstrated.

Zhang, Muyi↗