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Proceedings from symposia of the Technology 2004 Conference, November 8-10, 1994, Washington, DC. Volume 2 features papers on computers and software, virtual reality simulation, environmental technology, video and imaging, medical technology and life sciences, robotics and artificial intelligence, and electronics.
An advanced form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique, based on an eigenvalue decomposition of the background noise cross-spectral matrix, is robust against situations where isolated background auto-spectral levels are measured to be higher than levels of combined source and background signals. It also provides an alternate estimate of the cross-spectrum, which previously might have poor definition for low signal-to-noise ratio measurements. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels. Experimental results show limited success in recovering signal behavior for data where conventional background subtraction fails. They also demonstrate the new subtraction technique's ability to maintain a proper coherence relationship in the modified cross-spectral matrix. Beam-forming and de-convolution results indicate the method can successfully separate sources. Results also show a reduced need for the use of diagonal removal in phased array processing, at least for the limited data sets considered.
The project objective is to establish the capability to deposit multilayer structures for x-ray, neutron, and extreme ultraviolet (EUV) optic applications through the development of a magnetron sputtering deposition system. A specific goal of this endeavor is to combine multilayer deposition technology with the replication process in order to enhance NASA Marshall Space Flight Center's (MSFC's) position as a world leader in the design of innovative x-ray instrumentation through the development of full shell replicated multilayer optics. The development of multilayer structures are absolutely necessary in order to advance the field of x-ray astronomy by pushing the limit for observing the universe to ever-increasing photon energies (i.e., up to 200 keV or higher), well beyond Chandra's (approx.10 keV) and NuStar's (approx.75 keV) capability. The addition of multilayer technology would significantly enhance the x-ray optics capability at MSFC and allow NASA to maintain its world leadership position in the development, fabrication, and design of innovative x-ray instrumentation, which would be the first of its kind by combining multilayer technology with the mirror replication process. This marriage of these technologies would allow astronomers to see the universe in a new light by pushing to higher energies that are out of reach with today's instruments. To this aim, a magnetron vacuum sputter deposition system for the deposition of novel multilayer thin film x-ray optics is proposed. A significant secondary use of the vacuum deposition system includes the capability to fabricate multilayers for applications in the field of EUV optics for solar physics, neutron optics, and x-ray optics for a broad range of applications including medical imaging.
Individuals who experience decreases in load-bearing bone densities can be subject to a higher risk of bone fracture during daily activity. Astronauts may lose up to nine percent of their load-bearing bone density for every month they spend in space [1]. Because of this, specialized countermeasures reduce percent loss in bone density and reduce fracture risk upon returning to Earth. Astronauts will typically not be at risk for fracture during spaceflight, because of the lesser loads experienced in microgravity conditions. However, once back on Earth, astronauts have an increased risk for bone fracture as a result of weakened bone and return to 1G conditions [2]. It is therefore important to understand the significance of any bone density loss in addition to developing exercises in an attempt to limit losses in bone strength. NASA seeks to develop a deeper understanding of fracture risk through the development of a computational bone strength model to assess the bone fracture risk of astronauts pre-flight and post-flight. This study addresses the several key processes needed to develop such strength analyses using medical image processing and finite element modeling.
A subspace-based form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique is based on an eigenvalue decomposition of the background noise cross-spectral matrix. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels, and when background data do not match between measurements. Experimental results show limited success in recovering signal behavior for data in which conventional background subtraction fails. The results also demonstrate the subspace subtraction technique's ability to maintain a physical coherence relationship in the modified cross-spectral matrix. Deconvolution results from microphone phased array data indicate that array integration methods are largely insensitive to subtraction type, and that background subtraction with appropriate background data is an effective alternative to diagonal removal.
Traditionally, bowtie antennas have been known to exhibit wide impedance characteristics, omnidirectional radiation patterns, and linear polarization. There is a broad range of applications from medical imaging, archaeological survey, and Ground Penetrating Radar (GPR) to trackers and sensor networks where wideband bowtie antenna designs are required for their operations. Broadening the bandwidth of bowtie antenna requires widening the flare angle of the bowtie arms, which consequently results in a large surface area that may not be suitable for space-constrained applications. Moreover, drawback attributes of the wideband bowtie designs feature inconsistent radiation pattern across the bandwidth and low signal-to-noise (SNR) ratios. As it is known, the SNR would be improved in dual- or multi-band antennas due to their reduced bandwidth. To this end, dual-band/multi-band antennas are preferred over wideband antennas in applications where more than a single frequency of interest is present. Previously, a two-port double-dipole elements was reported, whose arms were orthogonally interleaved to facilitate operation in both the standard WLAN frequency bands (J. M. Steyn and et. al, Progress in Electromagnetic Research, Vol. – 10 pp. 151-161). Even though the antenna is not very compact it does exhibit good cross-polarization, moderate gain in both frequency bands. Another dual-band bowtie antenna which excites two bands using a single transmission line was reported (Wen Chao Zheng and et. al, IEEE Trans. Antennas propag., 2014). The design was compact and did not need multi-port feeding network. In this paper, a dual-band compact bowtie antenna operating at 900 MHz (RF band) and 2.45 GHz (ISM band) using a single excitation port is introduced. It is printed on a 1.54mm thick dielectric substrate (εr = 3.38). The antenna consists of two sets of bowtie arms, a microstrip transmission line to feed the bowtie arms, and a ground plane acting as a reflector to partially reduce the back radiation. One of the bowtie arms of each frequency is printed on the top layer and the other arm, which is mirror imaged, is printed on the bottom layer of the substrate. The length of the bowtie controls the resonance frequency of the antenna and the flare angle controls the bandwidth of the antenna. The microstrip transmission line, connected to a 50 Ω SMA probe, feeds the bowtie antenna. The compact antenna can be used for both RF and ISM band applications. The bowtie arms at the lower frequency band are miniaturized by elongating their electrical lengths. The influence of miniaturizing the bowtie arms and the supporting partial ground plane is observed in the reduced peak gain and degraded front-to-back ratio. These are partly neutralized using four quarter-wave choke-slots in the ground plane with two on each side of the feeding transmission line. The proposed antenna is numerically investigated and finalized by the finite-element based full-wave EM solver, ANSYS HFSS. The miniaturization has reduced the ground plane size by ~45% and the arms size by ~41%. In addition to the size reduction benefits, the antenna shows reasonable peak gain and front-to-back ratio in both the bands. The corresponding results will be presented and discussed at the conference.
Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.
Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.
Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.
Computer processing role in film scanning and digitizing for enhancing X ray and radioisotope scanner images in medical radiographs, discussing image noise reduction
In this Progress Report, we describe our continuing research activities concerning the development and implementation of advanced ultrasonic nondestructive evaluation methods applied to the inspection and characterization of complex composite structures. We explore the feasibility of implementing medical linear array imaging technology as a viable ultrasonic-based nondestructive evaluation method to inspect and characterize complex materials. As an initial step toward the application of linear array imaging technology to the interrogation of a wide range of complex composite structures, we present images obtained using an unmodified medical ultrasonic imaging system of two epoxy-bonded aluminum plate specimens, each with intentionally disbonded regions. These images are compared with corresponding conventional ultrasonic contact transducer measurements in order to assess whether these images can detect disbonded regions and provide information regarding the nature of the disbonded region. We present a description of a standoff/delay fixture which has been designed, constructed, and implemented on a Hewlett-Packard SONOS 1500 medical imaging system. This standoff/delay fixture, when attached to a 7.5 MHz linear array probe, greatly enhances our ability to interrogate flat plate specimens. The final section of this Progress Report describes a woven composite plate specimen that has been specially machined to include intentional flaws. This woven composite specimen will allow us to assess the feasibility of applying linear array imaging technology to the inspection and characterization of complex textile composite materials. We anticipate the results of this on-going investigation may provide a step toward the development of a rapid, real-time, and portable method of ultrasonic inspection and characterization based on linear array technology.
In this Progress Report, the author describes the continuing research to explore the feasibility of implementing medical linear array imaging technology as a viable ultrasonic-based nondestructive evaluation method to inspect and characterize complex materials. Images obtained using an unmodified medical ultrasonic imaging system of a bonded aluminum plate sample with a simulated disbond region are presented. The disbond region was produced by adhering a piece of plain white paper to a piece of cellophane tape and applying the paper-tape combination to one of the aluminum plates. Because the area under the paper was not adhesively bonded to the aluminum plate, this arrangement more closely simulates a disbond. Images are also presented for an aluminum plate sample with an epoxy strip adhered to one side to help provide information for the interpretation of the images of the bonded aluminum plate sample containing the disbond region. These images are compared with corresponding conventional ultrasonic contact transducer measurements in order to provide information regarding the nature of the disbonded region. The results of this on-going investigation may provide a step toward the development of a rapid, real-time, and portable method of ultrasonic inspection and characterization based on linear array technology. In Section 2 of this Progress Report, the preparation of the aluminum plate specimens is described. Section 3 describes the method of linear array imaging. Sections 4 and 5 present the linear array images and results from contact transducer measurements, respectively. A discussion of the results are presented in Section 6.
The characteristics of the Lixiscope when excited by X-rays produced by conventional electrically powered X-ray generators are explored to determine the optimum X-ray spectrum and mode of operation of the generator, which yields satisfactory Lixiscope images of medical and industrial specimens.
The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.
A heterogeneous material construction has been devised for sensing coils of superconducting quantum interference device (SQUID) magnetometers that are subject to a combination of requirements peculiar to some advanced applications, notably including low-field magnetic resonance imaging for medical diagnosis. The requirements in question are the following: The sensing coils must be large enough (in some cases having dimensions of as much as tens of centimeters) to afford adequate sensitivity; The sensing coils must be made electrically superconductive to eliminate Johnson noise (thermally induced noise proportional to electrical resistance); and Although the sensing coils must be cooled to below their superconducting- transition temperatures with sufficient cooling power to overcome moderate ambient radiative heat leakage, they must not be immersed in cryogenic liquid baths. For a given superconducting sensing coil, this combination of requirements can be satisfied by providing a sufficiently thermally conductive link between the coil and a cold source. However, the superconducting coil material is not suitable as such a link because electrically superconductive materials are typically poor thermal conductors. The heterogeneous material construction makes it possible to solve both the electrical- and thermal-conductivity problems. The basic idea is to construct the coil as a skeleton made of a highly thermally conductive material (typically, annealed copper), then coat the skeleton with an electrically superconductive alloy (typically, a lead-tin solder) [see figure]. In operation, the copper skeleton provides the required thermally conductive connection to the cold source, while the electrically superconductive coating material shields against Johnson noise that originates in the copper skeleton.
INTRODUCTION: Previous spaceflight experience and results from probabilistic risk assessment of spaceflight medical risk have highlighted the need for vital sign measurements, medical scopes, and clinical imaging tools for managing medical conditions during spaceflight. The Human Research Program’s Exploration Medical Capability (ExMC) Element and the Mars Campaign Office’s Exploration Medical Integrated Product Team (XMIPT) have performed ground-based evaluations of two Commercial-off-the-Shelf (COTS) Multi-functional Integrated Medical (MIM) devices, which integrate various medical capabilities together in one device. The key findings from these evaluations are presented in a complementary presentation, leaving this presentation to focus on forward recommendations for customized integration of multiple medical functionalities. KEY COMPONENTS: The key features of a custom integration of multiple medical functionalities includes devices and capabilities that optimally reduce medical risk. The COTS MIM devices incorporated functionality for best supporting Earth-based, emergency, pre-hospital care. Our custom integration will use probabilistic risk assessment tools, such as the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT), to determine the optimal functionality to include based on medical risk minimization. An additional feature of custom integration includes the ability to adapt to different requirements within different vehicles and/or missions. The COTS MIM devices store data in patient specific records, however, the format of the records is not modifiable, and data are not easily transferred from the MIM device to a central data architecture outside of the manufacturer’s established system. Our concept for custom integration will use devices that have an open application programming interface, which can easily connect to independent data architectures and third-party visualization software. The ultrasound capabilities included within the COTS MIM devices did not satisfy many of the Artemis Research and Operations Working Group’s ultrasound functional needs, and therefore, incorporation of higher quality ultrasound capabilities within a customized integration will be beneficial. The COTS MIM devices included minimal procedural guidance and clinical decision support tools. Supplemental tools of this type would need to be supplied along with the COTS MIM devices if they were to be used operationally, so another advantage of customization is the ability to integrate these support tools along with the medical functionality, for a more streamlined user experience. CONCLUSION: Investigation of a customized integration of medical functionality provides a method for further understanding the needs of a long-term exploration spaceflight medical system. The crew members of these exploration missions will need to operate more and more independently from Earth-based ground support. Therefore, having an optimized, streamlined medical system, which contains the functionality and supporting information needed, while remaining within mission and vehicle constraints, will help to maintain crew health and performance, which is necessary for achieving high levels of mission success.
Swept-frequency sound replaces pulsed sound. Ultrasonic medical instrument produces images of peripheral and coronary arteries with resolutions higher and at depths greater than attainable by previous ultrasonic systems. Time-delay-spectrometry imager includes scanning, image-processing, and displaying equipment. It sweeps in frequency from 0 to 10 MHz in 20 ms, pauses for 5 ms, and repeats sweep. Intended for use in noninvasive detection and measurement of atherosclerotic lesions.
Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.