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All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

A study of image quality for radar image processing

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics.

King, R. W.↗
NASA NTRS2011

Image Quality Indicator for Infrared Inspections

The quality of images generated during an infrared thermal inspection depends on many system variables, settings, and parameters to include the focal length setting of the IR camera lens. If any relevant parameter is incorrect or sub-optimal, the resulting IR images will usually exhibit inherent unsharpness and lack of resolution. Traditional reference standards and image quality indicators (IQIs) are made of representative hardware samples and contain representative flaws of concern. These standards are used to verify that representative flaws can be detected with the current IR system settings. However, these traditional standards do not enable the operator to quantify the quality limitations of the resulting images, i.e. determine the inherent maximum image sensitivity and image resolution. As a result, the operator does not have the ability to optimize the IR inspection system prior to data acquisition. The innovative IQI described here eliminates this limitation and enables the operator to objectively quantify and optimize the relevant variables of the IR inspection system, resulting in enhanced image quality with consistency and repeatability in the inspection application. The IR IQI consists of various copper foil features of known sizes that are printed on a dielectric non-conductive board. The significant difference in thermal conductivity between the two materials ensures that each appears with a distinct grayscale or brightness in the resulting IR image. Therefore, the IR image of the IQI exhibits high contrast between the copper features and the underlying dielectric board, which is required to detect the edges of the various copper features. The copper features consist of individual elements of various shapes and sizes, or of element-pairs of known shapes and sizes and with known spacing between the elements creating the pair. For example, filled copper circles with various diameters can be used as individual elements to quantify the image sensitivity limit. Copper line-pairs of various sizes where the line width is equivalent to the spacing between the lines can be used as element-pairs to quantify the image resolution limit.

Burke, Eric↗
NASA NTRS1976

Geometric assessment of image quality using digital image registration techniques

Image registration techniques were developed to perform a geometric quality assessment of multispectral and multitemporal image pairs. Based upon LANDSAT tapes, accuracies to a small fraction of a pixel were demonstrated. Because it is insensitive to the choice of registration areas, the technique is well suited to performance in an automatic system. It may be implemented at megapixel-per-second rates using a commercial minicomputer in combination with a special purpose digital preprocessor.

Tisdale, G. E.↗
NASA NTRS1976

Image quality prediction - An aid to the Viking lander imaging investigation on Mars

Image quality criteria and image quality predictions are formulated for the multispectral panoramic cameras carried by the Viking Mars landers. Image quality predictions are based on expected camera performance, Mars surface radiance, and lighting and viewing geometry (fields of view, Mars lander shadows, solar day-night alternation), and are needed in diagnosis of camera performance, in arriving at a preflight imaging strategy, and revision of that strategy should the need arise. Landing considerations, camera control instructions, camera control logic, aspects of the imaging process (spectral response, spatial response, sensitivity), and likely problems are discussed. Major concerns include: degradation of camera response by isotope radiation, uncertainties in lighting and viewing geometry and in landing site local topography, contamination of camera window by dust abrasion, and initial errors in assigning camera dynamic ranges (gains and offsets).

Huck, F. O.↗
DOE OSTI2019

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

Purpose: To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI. Materials and methods: This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm{sup 2}) and one higher b value (aHBV at 2000 s/mm{sup 2}). The acquired data were postprocessed to generate two different types of trace-weighted images—using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm{sup 2}) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm{sup 2}) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores. Results: Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm{sup 2} sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time). Conclusion: Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2011

Image Quality of the Helioseismic and Magnetic Imager (HMI) Onboard the Solar Dynamics Observatory (SDO)

We describe the imaging quality of the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) as measured during the ground calibration of the instrument. We describe the calibration techniques and report our results for the final configuration of HMI. We present the distortion, modulation transfer function, stray light,image shifts introduced by moving parts of the instrument, best focus, field curvature, and the relative alignment of the two cameras. We investigate the gain and linearity of the cameras, and present the measured flat field.

Solar Dynamics Observatory↗
NASA NTRS1995

A comparison of Image Quality Models and Metrics Predicting Object Detection

Many models and metrics for image quality predict image discriminability, the visibility of the difference between a pair of images. Some image quality applications, such as the quality of imaging radar displays, are concerned with object detection and recognition. Object detection involves looking for one of a large set of object sub-images in a large set of background images and has been approached from this general point of view. We find that discrimination models and metrics can predict the relative detectability of objects in different images, suggesting that these simpler models may be useful in some object detection and recognition applications. Here we compare three alternative measures of image discrimination, a multiple frequency channel model, a single filter model, and RMS error.

Rohaly, Ann Marie↗
DOE OSTI2019

Rapid kVp switching dual-energy CT in the assessment of urolithiasis in patients with large body habitus: preliminary observations on image quality and stone characterization

Purpose: The purpose of this study was to investigate the image quality (IQ) considerations of rapid kVp switching dual-energy CT (rsDECT) in the assessment of urolithiasis in patients with large body habitus and to evaluate whether it allows stone characterization. Materials and methods: In this IRB-approved, HIPAA compliant retrospective study, 93 consecutive patients (M/F = 72/21, mean age 56.9 years, range 23–83 years) with large body habitus (> 90 kg/198 lbs) who underwent dual-energy (DE) stone protocol CT on a rapid kVp switching DECT scanner between January 2013 and December 2016 were included. Scan acquisition protocol included an initial unenhanced single-energy CT (SECT) scan of KUB followed by targeted DECT in the region of stones. Two readers evaluated both CT data sets (axial 5 mm 120 kVp/140 kVp QC/70 keV monoenergetic, material density water/iodine images and coronal/sagittal 3 mm images) for the assessment of image quality (Scores: 1–4) and characterization of stone composition (reference standard: crystallography). Results: One hundred and five CT examinations were performed in 93 patients (mean body weight 105.12 ± 13.53 kg, range 91–154 kg), and a total of 321 urinary tract calculi (mean size-4.8 ± 3.2 mm, range 1.2–22 mm) were detected. Both SECT and targeted monoenergetic images were of acceptable image quality (mean IQ: 3.77 and 3.83, kappa 0.79 and 0.87 respectively). Material density water and iodine images had lower IQ scores (mean IQ: 2.97 and 3.09 respectively) with image quality deterioration due to severe photon starvation/streak artifacts in 20% (21/105) and 17% (18/105) scans, respectively. Characterization of stone composition into uric acid/non-uric acid stones was achieved in 93.14% (299/321) of calculi (mean size: 4.99 ± 3.3 mm, range 1.2–22 mm), while 7% (22/321) stones could not be characterized (mean size 3.03 ± 1.16 mm, range 1.6–6.4 mm) (p < 0.001). Most common reason for non-characterization was image quality deterioration of the material density iodine images due to severe photon starvation artifacts. On multivariate regression, stone size and patient weight were predictors of stone composition determination on DECT (p < 0.05). The transverse diameter had a weak negative correlation with stone composition determination, but it was not statistically significant. Stone characterization into uric acid vs. non-uric acid stones was accurate in 95% (n = 38/40) of stones in comparison with crystallography. Conclusion: In patients with large body habitus, rsDECT allowed characterization of most calculi (93%) despite image quality deterioration due to photon starvation/streak artifacts in up to 20% of material density images. Stone size and patient weight were predictors of stone composition determination on DECT, and small calculi in very large patients may not be characterized.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2015

Retinal Image Quality Assessment for Spaceflight-Induced Vision Impairment Study

Long-term exposure to space microgravity poses significant risks for visual impairment. Evidence suggests such vision changes are linked to cephalad fluid shifts, prompting a need to directly quantify microgravity-induced retinal vascular changes. The quality of retinal images used for such vascular remodeling analysis, however, is dependent on imaging methodology. For our exploratory study, we hypothesized that retinal images captured using fluorescein imaging methodologies would be of higher quality in comparison to images captured without fluorescein. A semi-automated image quality assessment was developed using Vessel Generation Analysis (VESGEN) software and MATLAB® image analysis toolboxes. An analysis of ten images found that the fluorescein imaging modality provided a 36% increase in overall image quality (two-tailed p=0.089) in comparison to nonfluorescein imaging techniques.

retina↗
DOE OSTI2019

Metal Artifact Reduction for Orthopedic Prosthesis in Lower Extremity CT Venography: Evaluation of Image Quality and Vessel Conspicuity

Purpose: This study evaluates the image quality of lower extremity CT venography reconstructed with orthopedic metal artifact reduction (O-MAR) in patients with unilateral or bilateral metallic prostheses in the hip or knee. Methods: This retrospective study was approved by our institutional review board, and informed consent was waived. Twenty-nine patients of lower extremity CT with 51 metallic hip or knee prostheses were reconstructed to both standard CT images and O-MAR images. The subjective image quality and vessel conspicuity for both images were evaluated by two readers using five-point scales (0–4). Vessel conspicuity scores of 3 or 4 were considered diagnostically acceptable. Image noise was measured in the air and subcutaneous fat. Results: O-MAR images showed significantly higher scores of subjective image quality (p < .001) and vessel conspicuity (p = .002) than standard CT images. Diagnostic acceptance of vessel conspicuity was not significantly different between O-MAR images and standard CT images (p = 1.000). O-MAR images showed significantly less image noise than conventional CT images (p < .001 for both air and subcutaneous fat). Conclusion: O-MAR may be an effective solution for the metal artifacts in lower extremity CT venography; however, the distance between prostheses and vessels affects the diagnostic acceptance in patients with metallic hip or knee prostheses. Level of Evidence: Level 4, Case Series.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Effect of low tube voltage and low iodine concentration abdominal CT on image quality and radiation dose in children: preliminary study

Purpose: To evaluate the image quality of a double-low protocol (low tube voltage and low iodine concentration) for abdominal CT in children. Materials and methods: The double-low protocol was compared to the conventional protocol in pediatric patients weighing less than 40 kg from May 2016 to December 2016. Double-low protocol (Group A, n = 18): tube voltage, 70 kVp; and iodine concentration,: 250 mgI/mL versus Conventional protocol (Group B, n = 13): tube voltage, 80–100 kVp; and iodine concentration, 350 mgI/mL. Mean attenuation, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between the two groups. Image contrast, noise, beam-hardening artifacts, and overall image quality were subjectively scored. Reader performance for correctly differentiating two groups by visual assessment was evaluated. Radiation dose and total iodine load were recorded. Results: The mean attenuations of the portal vein and liver and the mean image noise in Group A were higher than in Group B (p = 0.04, 0.03, 0.004, respectively). The mean SNR and CNR of the main portal vein and liver were lower in Group A without any statistically significant difference. There were no statistically significant differences between the two groups in qualitative analysis (image contrast, image noise, and overall image quality) with substantial agreement between the reviewers (weighted kappa values; 0.59–0.76). Significantly diminished radiation dose and iodine load were observed in Group A compared with Group B (25.0%, 36.8% reduction; p = 0.007, 0.006, respectively). Conclusion: The double-low protocol was feasible for pediatric abdominal CT and reduced both radiation dose and iodine load, while maintaining image quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1976

Prediction of Viking lander camera image quality

Formulations are presented that permit prediction of image quality as a function of camera performance, surface radiance properties, and lighting and viewing geometry. Predictions made for a wide range of surface radiance properties reveal that image quality depends strongly on proper camera dynamic range command and on favorable lighting and viewing geometry. Proper camera dynamic range commands depend mostly on the surface albedo that will be encountered. Favorable lighting and viewing geometries depend mostly on lander orientation with respect to the diurnal sun path over the landing site, and tend to be independent of surface albedo and illumination scattering function. Side lighting with low sun elevation angles (10 to 30 deg) is generally favorable for imaging spatial details and slopes, whereas high sun elevation angles are favorable for measuring spectral reflectances.

Huck, F. O.↗
NASA NTRS2002

Effects of characteristics of image quality in an immersive environment

Image quality issues such as field of view (FOV) and resolution are important for evaluating "presence" and simulator sickness (SS) in virtual environments (VEs). This research examined effects on postural stability of varying FOV, image resolution, and scene content in an immersive visual display. Two different scenes (a photograph of a fountain and a simple radial pattern) at two different resolutions were tested using six FOVs (30, 60, 90, 120, 150, and 180 deg.). Both postural stability, recorded by force plates, and subjective difficulty ratings varied as a function of FOV, scene content, and image resolution. Subjects exhibited more balance disturbance and reported more difficulty in maintaining posture in the wide-FOV, high-resolution, and natural scene conditions.

Non-NASA Center↗
DOE OSTI2019

Weight-adapted ultra-low-dose pancreatic perfusion CT: radiation dose, image quality, and perfusion parameters

Purpose: We evaluate the reliability and feasibility of weight-adapted ultra-low-dose pancreatic perfusion CT. Methods: A total of 100 (47 men, 53 women) patients were enrolled prospectively and were assigned to five groups (A, B, C, D, and E) with different combination of tube voltage and tube current according to their body weight. Radiation dose parameters including volume CT dose index (CTDI) and dose-length product (DLP) were recorded. Image quality was evaluated both subjectively and objectively (noise, signal-to-noise ratio, contrast-to-noise ratio). Perfusion parameters including blood flow (BF), blood volume (BV), and permeability (PMB) were measured. The dose, image quality measurements, and perfusion parameters were compared between the five groups using one-way analysis of variance (ANOVA). Results: Radiation dose reached 8.7 mSv in patients under 50 kg and was 18.9 mSv in patients above 80 kg. The mean subjective image quality score was above 4.45 on a 5-point scale with good agreement between two radiologists. Groups A–D had equivalent performance on objective image quality (P > 0.05), while Group E performed even better (P < 0.05). No significant differences emerged in comparison with perfusion parameters (BF, BV, PMB) of normal pancreas parenchyma between the five groups. Conclusion: Weight-adapted ultra-low-dose pancreatic perfusion CT can effectively reduce radiation dose without prejudice to image quality, and the perfusion parameters of normal parenchyma are accurate and reliable.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Evaluating Machine Learning-Based MRI Reconstruction Using Digital Image Quality Phantoms

Quantitative and objective evaluation tools are essential for assessing the performance of machine learning (ML)-based magnetic resonance imaging (MRI) reconstruction methods. However, the commonly used fidelity metrics, such as mean squared error (MSE), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR), often fail to capture fundamental and clinically relevant MR image quality aspects. To address this, we propose evaluation of ML-based MRI reconstruction using digital image quality phantoms and automated evaluation methods. Our phantoms are based upon the American College of Radiology (ACR) large physical phantom but created in k-space to simulate their MR images, and they can vary in object size, signal-to-noise ratio, resolution, and image contrast. Our evaluation pipeline incorporates evaluation metrics of geometric accuracy, intensity uniformity, percentage ghosting, sharpness, signal-to-noise ratio, resolution, and low-contrast detectability. We demonstrate the utility of our proposed pipeline by assessing an example ML-based reconstruction model across various training and testing scenarios. The performance results indicate that training data acquired with a lower undersampling factor and coils of larger anatomical coverage yield a better performing model. The comprehensive and standardized pipeline introduced in this study can help to facilitate a better understanding of the performance and guide future development and advancement of ML-based reconstruction algorithms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Comparison of image noise and image quality between full-dose abdominal computed tomography scans reconstructed with weighted filtered back projection and half-dose scans reconstructed with improved sinogram-affirmed iterative reconstruction (SAFIRE*)

Purpose: To retrospectively compare the image noise, signal-to-noise ratio (SNR), and subjective image quality between CT images acquired with a dual-source, split-dose imaging protocol reconstructed at full and half doses with weighted filtered back projection (wFBP) and an improved sinogram-affirmed iterative reconstruction algorithm (SAFIRE*). Methods: Fifty-three consecutive patients underwent contrast-enhanced CT of the abdomen using a standardized dual-source, single energy CT protocol. Half-dose images were retrospectively generated using data from one detector only. Full-dose datasets were reconstructed with wFBP, while half-dose datasets were reconstructed with wFBP and SAFIRE* strengths 1–5. Region of interest analysis was performed to assess SNR and noise. Diagnostic acceptability, subjective noise, and spatial resolution were graded on a 10-point scale by two readers. Statistical analysis was carried out with repeated measures analysis of variance, Wilcoxon signed rank test, and Cohen’s κ test. Results: With the increasing strengths of SAFIRE*, a progressive reduction in noise and increase in SNR (p < 0.01) was observed. There was a statistically significant decrease in objective noise and increase in SNR in half-dose SAFIRE* strength 4 and 5 reconstructions compared to full-dose reconstructions using wFBP (p < 0.01). Qualitative analysis revealed a progressive increase in diagnostic acceptability, decrease in subjective noise and increase in spatial resolution for half-dose images reconstructed with the increasing strengths of SAFIRE* (p < 0.01). Conclusions: Half-dose CT images reconstructed with SAFIRE* at strength 4 and 5 have superior image quality compared to full-dose images reconstructed with wFBP. SAFIRE* potentially allows dose reductions in the order of 50% over wFBP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗