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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

An investigation of kV CBCT image quality and dose reduction for volume-of-interest imaging using dynamic collimation

Purpose: The focus of this work was to investigate the improvements in image quality and dose reduction for volume-of-interest (VOI) kilovoltage-cone beam CT (CBCT) using dynamic collimation. Methods: A prototype iris aperture was used to track a VOI during a CBCT acquisition. The current aperture design is capable of 1D translation as a function of gantry angle and dynamic adjustment of the iris radius. The aperture occupies the location of the bow-tie filter on a Varian On-Board Imager system. CBCT and planar image quality were investigated as a function of aperture radius, while maintaining the same dose to the VOI, for a 20 cm diameter cylindrical water phantom with a 9 mm diameter bone insert centered on isocenter. Corresponding scatter-to-primary ratios (SPR) were determined at the detector plane with Monte Carlo simulation using EGSnrc. Dose distributions for various sizes VOI were modeled using a dynamic BEAMnrc library and DOSXYZnrc. The resulting VOI dose distributions were compared to full-field distributions. Results: SPR was reduced by a factor of 8.4 when decreasing iris diameter from 21.2 to 2.4 cm (at isocenter). Depending upon VOI location and size, dose was reduced to 16%–90% of the full-field value along the central axis plane and down to 4% along the axis of rotation, while maintaining the same dose to the VOI compared to full-field techniques. When maintaining constant dose to the VOI, this change in iris diameter corresponds to a factor increase of approximately 1.6 in image contrast and a factor decrease in image noise of approximately 1.2. This results in a measured gain in contrast-to-noise ratio by a factor of approximately 2.0. Conclusions: The presented VOI technique offers improved image quality for image-guided radiotherapy while sparing the surrounding volume of unnecessary dose compared to full-field techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature-based image registration in range-image guided radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-05: Multidimensional Imaging Radiomics-Geodesics: A Novel Manifold Learning Based Automatic Feature Extraction Method for Diagnostic Prediction in Multiparametric Imaging

Purpose: Multiparametric radiological imaging is used for diagnosis in patients. Potentially extracting useful features specific to a patient’s pathology would be crucial step towards personalized medicine and assessing treatment options. In order to automatically extract features directly from multiparametric radiological imaging datasets, we developed an advanced unsupervised machine learning algorithm called the multidimensional imaging radiomics-geodesics(MIRaGe). Methods: Seventy-six breast tumor patients underwent 3T MRI breast imaging were used for this study. We tested the MIRaGe algorithm to extract features for classification of breast tumors into benign or malignant. The MRI parameters used were T1-weighted, T2-weighted, dynamic contrast enhanced MR imaging (DCE-MRI) and diffusion weighted imaging(DWI). The MIRaGe algorithm extracted the radiomics-geodesics features (RGFs) from multiparametric MRI datasets. This enable our method to learn the intrinsic manifold representations corresponding to the patients. To determine the informative RGF, a modified Isomap algorithm(t-Isomap) was created for a radiomics-geodesics feature space(tRGFS) to avoid overfitting. Final classification was performed using SVM. The predictive power of the RGFs was tested and validated using k-fold cross validation. Results: The RGFs extracted by the MIRaGe algorithm successfully classified malignant lesions from benign lesions with a sensitivity of 93% and a specificity of 91%. The top 50 RGFs identified as the most predictive by the t-Isomap procedure were consistent with the radiological parameters known to be associated with breast cancer diagnosis and were categorized as kinetic curve characterizing RGFs, wash-in rate characterizing RGFs, wash-out rate characterizing RGFs and morphology characterizing RGFs. Conclusion: In this paper, we developed a novel feature extraction algorithm for multiparametric radiological imaging. The results demonstrated the power of the MIRaGe algorithm at automatically discovering useful feature representations directly from the raw multiparametric MRI data. In conclusion, the MIRaGe informatics model provides a powerful tool with applicability in cancer diagnosis and a possibility of extension to other kinds of pathologies. NIH (P50CA103175, 5P30CA006973 (IRAT), R01CA190299, U01CA140204), Siemens Medical Systems (JHU-2012-MR-86-01) and Nivida Graphics Corporation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-AB-BRA-07: Low Dose Imaging with Avalanche Amorphous Selenium Flat Panel Imager

Purpose: We present the first active matrix flat panel imager (AMFPI) capable of producing x-ray quantum noise limited images at low doses by overcoming the electronic noise through signal amplification by photoconductive avalanche gain (gav). The indirect detector fabricated uses an optical sensing layer of amorphous selenium (a-Se) known as High-Gain Avalanche Rushing Photoconductor (HARP). The detector design is called Scintillator HARP (SHARP)-AMFPI. This is the first image sensor to utilize solid-state HARP technology. Methods: The detector’s electronic readout is a 24 × 30 cm{sup 2} array of thin film transistors (TFT) with a pixel pitch of 85 µm. The HARP structure consists of a 15 µm layer of a-Se isolated from the high voltage (HV) and signal electrode by a 2 µm thick hole blocking layer and electron blocking layer, respectively, to reduce dark current. A 150 µm thick structured CsI scintillator with reflective backing and a fiber optic faceplate (FOP) was coupled to the semi-transparent HV bias electrode of the HARP structure. Images were acquired using a 30 kVp Mo/Mo spectrum typically used in mammography. Results: Optical sensitivity measurements demonstrate that gav = 76 ± 5 can be achieved over the entire active area of the detector. At a constant dose to the detector of 6.67 µGy, image quality increases with gav until the effective electronic noise is negligible. Quantum noise limited images can be obtained with doses as low as 0.18 µGy. Conclusion: We demonstrate the feasibility of utilizing avalanche gain to overcome electronic noise. The indirect detector fabricated is the first solid-state imaging sensor to use HARP, and the largest active area HARP sensor to date. Our future work is to improve charge transport within the HARP structure and utilize a transparent HV electrode.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internal features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The Senior Author receives financial support from Siemens GmbH Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A Heuristic Approach to Remove the Background Intensity on White-light Solar Images. I. STEREO /HI-1 Heliospheric Images

White-light coronal and heliospheric imagers observe scattering of photospheric light from both dust particles (the F-Corona) and free electrons in the corona (the K-corona). The separation of the two coronae is thus vitally important to reveal the faint K-coronal structures (e.g., streamers, co-rotating interaction regions, coronal mass ejections, etc.). However, the separation of the two coronae is very difficult, so we are content in defining a background corona that contains the F- and as little K- as possible. For both the LASCO-C2 and LASCO-C3 coronagraphs aboard the Solar and Heliospheric Observatory ( SOHO ) and the white-light imagers of the SECCHI suite aboard the Solar Terrestrial Relationships Observatory ( STEREO ), a time-dependent model of the background corona is generated from about a month of similar images. The creation of such models is possible because the missions carrying these instruments are orbiting the Sun at about 1 au. However, the orbit profiles for the upcoming Solar Orbiter and Solar Probe Plus missions are very different. These missions will have elliptic orbits with a rapidly changing radial distance, hence invalidating the techniques in use for the SOHO /LASCO and STEREO /SECCHI instruments. We have been investigating techniques to generate background models out of just single images that could be used for the Solar Orbiter Heliospheric Imager and the Wide-field Imager for the Solar Probe Plus packages on board the respective spacecraft. In this paper, we introduce a state-of-the-art, heuristic technique to create the background intensity models of STEREO /HI-1 data based solely on individual images, report on new results derived from its application, and discuss its relevance to instrumental and operational issues.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Development of Simultaneous Beta-and-Coincidence-Gamma Imager for Plant Imaging Research

The goal of this project is to develop a novel imaging system that can simultaneously acquire beta and coincidence gamma images of positron sources in thin objects such as leaves of plants. This hybrid imager can be used to measure carbon assimilation in plants quantitatively and in real-time after C-11 labeled carbon-dioxide is administered. A better understanding of carbon assimilation, particularly under the increasingly elevated atmospheric CO 2 level, is extremely critical for plant scientists who study food crop and biofuel production. Phase 1 of this project is focused on the technology development with 3 specific aims: (1) develop a hybrid detector that can detect beta and gamma rays simultaneously; (2) develop an imaging system that can differentiate these two types of radiation and acquire beta and coincidence gamma images in real-time; (3) develop techniques to quantify radiotracer distribution using beta and gamma images. Phase 2 of this project is to apply technologies developed in phase 1 to study plants using positron-emitting radionuclide such as 11 C to study carbon assimilation in biofuel plants.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Full-Depth Coadds of the WISE and First-Year NEOWISE-Reactivation Images

The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE) Reactivation mission released data from its first full year of observations in 2015. This data set includes ~2.5 million exposures in each of W1 and W2, effectively doubling the amount of WISE imaging available at 3.4 μm and 4.6 μm relative to the AllWISE release. In this paper, we have created the first ever full-sky set of coadds combining all publicly available W1 and W2 exposures from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We employ an adaptation of the unWISE image coaddition framework, which preserves the native WISE angular resolution and is optimized for forced photometry. By incorporating two additional scans of the entire sky, we not only improve the W1/W2 depths, but also largely eliminate time-dependent artifacts such as off-axis scattered moonlight. We anticipate that our new coadds will have a broad range of applications, including target selection for upcoming spectroscopic cosmology surveys, identification of distant/massive galaxy clusters, and discovery of high-redshift quasars. In particular, our full-depth AllWISE+NEOWISER coadds will be an important input for the Dark Energy Spectroscopic Instrument selection of luminous red galaxy and quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction pipelines. Finally, much more work still remains in order to fully leverage NEOWISER imaging for astrophysical applications beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Atomic Force Microscope Controlled Topographical Imaging and Proximal Probe Thermal Desorption/Ionization Mass Spectrometry Imaging

This paper reports on the development of a hybrid atmospheric pressure atomic force microscopy/mass spectrometry imaging system utilizing nano-thermal analysis probes for thermal desorption surface sampling with subsequent atmospheric pressure chemical ionization and mass analysis. The basic instrumental setup and the general operation of the system were discussed and optimized performance metrics were presented. The ability to correlate topographic images of a surface with atomic force microscopy and a mass spectral chemical image of the same surface, utilizing the same probe without moving the sample from the system, was demonstrated. Co-registered mass spectral chemical images and atomic force microscopy topographical images were obtained from inked patterns on paper as well as from a living bacterial colony on an agar gel. Spatial resolution of the topography images based on pixel size (0.2 m x 0.8 m) was better than the resolution of the mass spectral images (2.5 m x 2.0 m), which were limited by current mass spectral data acquisition rate and system detection levels.

Ovchinnikova, Olga S↗
DOE OSTI2016

Imaging Taurine in the Central Nervous System Using Chemically Specific X-ray Fluorescence Imaging at the Sulfur K-Edge

A method to image taurine distributions within the central nervous system and other organs has long been sought. Since taurine is small and mobile, it cannot be chemically “tagged” and imaged using conventional immuno-histochemistry methods. Combining numerous indirect measurements, taurine is known to play critical roles in brain function during health and disease and is proposed to act as a neuro-osmolyte, neuro-modulator, and possibly a neuro-transmitter. Elucidation of taurine’s neurochemical roles and importance would be substantially enhanced by a direct method to visualize alterations, due to physiological and pathological events in the brain, in the local concentration of taurine at or near cellular spatial resolution in vivo or in situ in tissue sections. We thus have developed chemically specific X-ray fluorescence imaging (XFI) at the sulfur K-edge to image the sulfonate group in taurine in situ in ex vivo tissue sections. To our knowledge, this represents the first undistorted imaging of taurine distribution in brain at 20 μm resolution. We report quantitative technique validation by imaging taurine in the cerebellum and hippocampus regions of the rat brain. Further, we apply the technique to image taurine loss from the vulnerable CA1 (cornus ammonis 1) sector of the rat hippocampus following global brain ischemia. Furthermore, the location-specific loss of taurine from CA1 but not CA3 neurons following ischemia reveals osmotic stress may be a key factor in delayed neurodegeneration after a cerebral ischemic insult and highlights the significant potential of chemically specific XFI to study the role of taurine in brain disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
DOE OSTI2016

Coincident Aerosol and H2O Retrievals versus HSI Imager Field Campaign ReportH2O Retrievals versus HSI Imager Field Campaign Report

Two spectrally calibrated tarpaulins (tarps) were co-located at a fixed Global Positioning System (GPS) position on the gravel antenna field at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. Their placement was timed to coincide with the overflight of a new hyperspectral imaging satellite. The intention was to provide an analysis of the data obtained, including the measured and retrieved spectral albedos for the calibration tarps. Subsequently, a full suite of retrieved values of H2O column, and the aerosol overburden, were to be compared to those determined by alternate SGP ground truth assets. To the extent possible, the down-looking cloud images would be assessed against the all-sky images. Because cloud contamination above a certain level precludes the inversion processing of the satellite data, coupled with infrequent targeting opportunities, clear-sky conditions were imposed. The SGP site was chosen not only as a target of opportunity for satellite validation, but as perhaps the best coincident field measurement site, as established by DOE’s ARM Facility. The satellite team had every expectation of using the information obtained from the SGP to improve the inversion products for all subsequent satellite images, including the cloud and radiative models and parameterizations and, thereby, the performance assessment for subsequent and historic image collections. Coordinating with the SGP onsite team, four visits, all in 2009, to the Central Facility occurred: • June 6-8 (successful exploratory visit to plan tarp placements, etc.) • July 18-24 (canceled because of forecast for heavy clouds) • Sep 9-12 (ground tarps placed, onset of clouds) • Nov 7-9 (visit ultimately canceled because of weather predictions). As noted, in each instance, any significant overcast prediction precluded image collection from the satellite. Given the long task-scheduling procedures (which were in place for each time period), coupled with other priorities and the satellite lifetime, no alternate SGP images could be obtained.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

High compression image and image sequence coding

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Kunt, Murat↗
NASA NTRS1992

Astro-1 ultraviolet imaging of the 30 Doradus and SN 1987A fields with the Ultraviolet Imaging Telescope

A preliminary analysis of Ultraviolet Imaging Telescope (UIT) images in the 30 Doradus region is reported. Photometry was obtained for the 30 Doradus cluster and its UV-bright core, R136, in various UIT bandpasses. It is found that about 14 percent of the total FUV light and about 16 percent of the total near-UV light of the 3-arcmin diameter 30 Doradus cluster originates from the region within 5 arcsec of R136. The UV magnitudes and colors of R136 and other known O and Wolf-Rayet WN stars in the same field were measured. The UIT data, combined with published observations at longer wavelengths, indicate that R136a1, the brightest component of R136, is not a supermassive stars. A qualitative comparison between the UIT images, Einstein X-ray data, IRAS HiRes images, and ground-based CCD images in forbidden O III 5007 A, H-alpha, B, R, U, and Stromgren u is performed. The extended diffuse UV feature detected in the UIT images is correlated with the IR structure seen in the IRAS 60-micron HiRes image, which suggests the existence of large amounts of widely distributed dust in this region.

Cheng, Kwang-Ping↗
NASA NTRS1992

Instrument requirements for imaging the magnetosphere in extreme-ultraviolet and energetic neutral atoms derived from computer-simulated images

Scientific requirements for He(+)(304 A) and energetic neutral atom (ENA) magnetospheric imaging, as well as the derived instrumental requirements are presented. Both ENA imaging of the hot plasma and EUV imaging of the cold plasma are highlighted. The question of the accuracy with which physically significant parameters can be extracted from actual images using computerized algorithms is addressed. An example of an ENA image analyzed by means of the Powell minimization algorithm is given. Automated unfolding of global magnetospheric images is also discussed. A Mercator projection of a model INA image is shown.

Roelof, Edmond C.↗