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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Technical Note: Evaluation of a 160-mm/256-row CT scanner for whole-heart quantitative myocardial perfusion imaging

Purpose: The authors investigated the performance of a recently introduced 160-mm/256-row CT system for low dose quantitative myocardial perfusion (MP) imaging of the whole heart. This platform is equipped with a gantry capable of rotating at 280 ms per full cycle, a second generation of adaptive statistical iterative reconstruction (ASiR-V) to correct for image noise arising from low tube voltage potential/tube current dynamic scanning, and image reconstruction algorithms to tackle beam-hardening, cone-beam, and partial-scan effects. Methods: Phantom studies were performed to investigate the effectiveness of image noise and artifact reduction with a GE Healthcare Revolution CT system for three acquisition protocols used in quantitative CT MP imaging: 100, 120, and 140 kVp/25 mAs. The heart chambers of an anthropomorphic chest phantom were filled with iodinated contrast solution at different concentrations (contrast levels) to simulate the circulation of contrast through the heart in quantitative CT MP imaging. To evaluate beam-hardening correction, the phantom was scanned at each contrast level to measure the changes in CT number (in Hounsfield unit or HU) in the water-filled region surrounding the heart chambers with respect to baseline. To evaluate cone-beam artifact correction, differences in mean water HU between the central and peripheral slices were compared. Partial-scan artifact correction was evaluated from the fluctuation of mean water HU in successive partial scans. To evaluate image noise reduction, a small hollow region adjacent to the heart chambers was filled with diluted contrast, and contrast-to-noise ratio in the region before and after noise correction with ASiR-V was compared. The quality of MP maps acquired with the CT system was also evaluated in porcine CT MP studies. Myocardial infarct was induced in a farm pig from a transient occlusion of the distal left anterior descending (LAD) artery with a catheter-based interventional procedure. MP maps were generated from the dynamic contrast-enhanced (DCE) heart images taken at baseline and three weeks after the ischemic insult. Results: Their results showed that the phantom and animal images acquired with the CT platform were minimally affected by image noise and artifacts. For the beam-hardening phantom study, changes in water HU in the wall surrounding the heart chambers greatly reduced from >±30 to ≤ ± 5 HU at all kVp settings except one region at 100 kVp (7 HU). For the cone-beam phantom study, differences in mean water HU from the central slice were less than 5 HU at two peripheral slices with each 4 cm away from the central slice. These findings were reproducible in the pig DCE images at two peripheral slices that were 6 cm away from the central slice. For the partial-scan phantom study, standard deviations of the mean water HU in 10 successive partial scans were less than 5 HU at the central slice. Similar observations were made in the pig DCE images at two peripheral slices with each 6 cm away from the central slice. For the image noise phantom study, CNRs in the ASiR-V images were statistically higher (p < 0.05) than the non-ASiR-V images at all kVp settings. MP maps generated from the porcine DCE images were in excellent quality, with the ischemia in the LAD territory clearly seen in the three orthogonal views. Conclusions: The study demonstrates that this CT system can provide accurate and reproducible CT numbers during cardiac gated acquisitions across a wide axial field of view. This CT number fidelity will enable this imaging tool to assess contrast enhancement, potentially providing valuable added information beyond anatomic evaluation of coronary stenoses. Furthermore, their results collectively suggested that the 100 kVp/25 mAs protocol run on this CT system provides sufficient image accuracy at a low radiation dose (<3 mSv) for whole-heart quantitative CT MP imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-207B-11: Objective Image Characterization of Spectral CT with a Dual-Layer Detector

Purpose: To obtain objective reference data for the spectral performance on a dual-layer detector CT platform (IQon, Philips) and compare virtual monoenergetic to conventional CT images. Methods: Scanning was performed using the hospital’s clinical adult body protocol: helical acquisition at 120kVp, with CTDIvol=15mGy. Multiple modules (591, 515, 528) of a CATPHAN 600 phantom and a 20 cm diameter cylindrical water phantom were scanned. No modifications to the standard protocol were necessary to enable spectral imaging. Both conventional and virtual monoenergetic images were generated from acquired data. Noise characteristics were assessed through Noise Power Spectra (NPS) and pixel standard deviation from water phantom images. Spatial resolution was evaluated using Modulation Transfer Functions (MTF) of a tungsten wire as well as resolution bars. Low-contrast detectability was studied using contrast-to-noise ratio (CNR) of a low contrast object. Results: MTF curves of monoenergetic and conventional images were almost identical. MTF 50%, 10%, and 5% levels for monoenergetic images agreed with conventional images within 0.05lp/cm. These observations were verified by the resolution bars, which were clearly resolved at 7lp/cm but started blurring at 8lp/cm for this protocol in both conventional and 70 keV images. NPS curves indicated that, compared to conventional images, the noise power distribution of 70 keV monoenergetic images is similar (i.e. noise texture is similar) but exhibit a low frequency peak at keVs higher and lower than 70 keV. Standard deviation measurements show monoenergetic images have lower noise except at 40 keV where it is slightly higher. CNR of monoenergetic images is mostly flat across keV values and is superior to that of conventional images. Conclusion: Values for standard image quality metrics are the same or better for monoenergetic images compared to conventional images. Results indicate virtual monoenergetic images can be used without any loss in image quality or noise penalties relative to conventional images. This study was performed as part of a research agreement among Philips Healthcare, University Hospitals of Cleveland, and Case Western Reserve University.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Diversity imaging techniques in lidar

Diversity imaging techniques have been successfully employed in conventional microwave range-Doppler imaging radars to obtain high resolution images of both natural and man-made targets. These techniques allow microwave radars to achieve image resolution which would otherwise require excessively large antennas. Recent advances in coherent laser radar techniques and signal processing have led to the development of range-Doppler imaging laser radars. While much of the theory and signal processing techniques used in microwave radars can be brought to bear on laser radars, the significant difference in wavelength results in issues peculiar to laser radar systems. Both the fundamental concepts and specific applications of diversity imaging techniques applied to laser radar imaging systems will be discussed. Angle, frequency, and bistatic angle degrees of freedom can be employed in a coherent laser radar imaging system to achieve image resolution which exceeds the traditional Rayleigh criterion associated with the receive aperture. In diversity imaging, angle and frequency degrees of freedom can be used to synthesize an effective aperture providing range and Doppler target information. The ability to vary the bistatic angle provides an additional means of synthesizing an effective aperture. Both simulated and experimentally obtained laser radar images of spinning and/or tumbling objects utilizing both angular and frequency diversity will be presented. In coherent laser radar systems, image quality can be dominated by laser speckle effects. In particular, the signal-to-noise ratio (SNR) of a coherent laser radar image is at most unity in the presence of fully developed speckle. Diversity techniques can be utilized to improve the image SNR; simple incoherent averaging of images utilizing temporal and polarization degrees of freedom can significantly improve image SNR. Both the SNR and image resolution (as defined by the synthetic aperture) contribute to image quality. The relationship between the available degrees of freedom and image quality are discussed.

Schultz, K. I.↗
NASA NTRS2008

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Wemet, Mark P.↗
NASA NTRS2012

Smart Image Enhancement Process

Contrast and lightness measures are used to first classify the image as being one of non-turbid and turbid. If turbid, the original image is enhanced to generate a first enhanced image. If non-turbid, the original image is classified in terms of a merged contrast/lightness score based on the contrast and lightness measures. The non-turbid image is enhanced to generate a second enhanced image when a poor contrast/lightness score is associated therewith. When the second enhanced image has a poor contrast/lightness score associated therewith, this image is enhanced to generate a third enhanced image. A sharpness measure is computed for one image that is selected from (i) the non-turbid image, (ii) the first enhanced image, (iii) the second enhanced image when a good contrast/lightness score is associated therewith, and (iv) the third enhanced image. If the selected image is not-sharp, it is sharpened to generate a sharpened image. The final image is selected from the selected image and the sharpened image.

Jobson, Daniel J.↗
DOE OSTI2015

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT

Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240{sup ∘} short scan angular span was divided into four consecutive 60{sup ∘} angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200{sup ∘}, three 66{sup ∘} angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60{sup ∘} angular subsectors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Generation of hybrid sinograms for the recovery of kV-CT images with metal artifacts for helical tomotherapy

Purpose: The overall goal of this study is to restore kilovoltage computed tomography (kV-CT) images which are disfigured by patients’ metal prostheses. By generating a hybrid sinogram that is a combination of kV and megavoltage (MV) projection data, the authors suggest a novel metal artifact-reduction (MAR) method that retains the image quality to match that of kV-CT and simultaneously restores the information of metal prostheses lost due to photon starvation. Methods: CT projection data contain information about attenuation coefficients and the total length of the attenuation. By normalizing raw kV projections with their own total lengths of attenuation, mean attenuation projections were obtained. In the same manner, mean density projections of MV-CT were obtained by the normalization of MV projections resulting from the forward projection of density-calibrated MV-CT images with the geometric parameters of the kV-CT device. To generate the hybrid sinogram, metal-affected signals of the kV sinogram were identified and replaced by the corresponding signals of the MV sinogram following a density calibration step with kV data. Filtered backprojection was implemented to reconstruct the hybrid CT image. To validate the authors’ approach, they simulated four different scenarios for three heads and one pelvis using metallic rod inserts within a cylindrical phantom. Five inserts describing human body elements were also included in the phantom. The authors compared the image qualities among the kV, MV, and hybrid CT images by measuring the contrast-to-noise ratio (CNR), the signal-to-noise ratio (SNR), the densities of all inserts, and the spatial resolution. In addition, the MAR performance was compared among three existing MAR methods and the authors’ hybrid method. Finally, for clinical trials, the authors produced hybrid images of three patients having dental metal prostheses to compare their MAR performances with those of the kV, MV, and three existing MAR methods. Results: The authors compared the image quality and MAR performance of the hybrid method with those of other imaging modalities and the three MAR methods, respectively. The total measured mean of the CNR (SNR) values for the nonmetal inserts was determined to be 14.3 (35.3), 15.3 (37.8), and 25.5 (64.3) for the kV, MV, and hybrid images, respectively, and the spatial resolutions of the hybrid images were similar to those of the kV images. The measured densities of the metal and nonmetal inserts in the hybrid images were in good agreement with their true densities, except in cases of extremely low densities, such as air and lung. Using the hybrid method, major streak artifacts were suitably removed and no secondary artifacts were introduced in the resultant image. In clinical trials, the authors verified that kV and MV projections were successfully combined and turned into the resultant hybrid image with high image contrast, accurate metal information, and few metal artifacts. The hybrid method also outperformed the three existing MAR methods with regard to metal information restoration and secondary artifact prevention. Conclusions: The authors have shown that the hybrid method can restore the overall image quality of kV-CT disfigured by severe metal artifacts and restore the information of metal prostheses lost due to photon starvation. The hybrid images may allow for the improved delineation of structures of interest and accurate dose calculations for radiation treatment planning for patients with metal prostheses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-204: Radiation Dose to Patients Resulting From Image Guidance Procedures and AAPM TG-180 Update

Purpose: Image-guided radiation therapy (IGRT) is the new paradigm for patient positioning and target localization in radiotherapy. Daily imaging procedures add additional dose to the patient's treatment volume and normal tissues and may expose the organs at risk to unaccounted doses. This presentation is to update the progress of AAPM TG-180 which aims to provide strategies to quantify and account the dose from both MV and kV imaging in patient treatment planning. Methods: Our current knowledge on image guidance dose is presented. A summary of doses from image guidance procedures delivered to patients in relationship with therapeutic doses is given. Different techniques in reducing the image guidance dose are summarized. Typical organ doses resulting from different image acquisition procedures used in IGRT are tabulated. Results: Many techniques to reduce the imaging doses are available in clinical applications. There are large variations between dose to bone and dose to soft tissues for x-rays at kilovoltage energy range. Methods for clinical implementation of accounting for the imaging dose from an imaging procedure are available. Beam data from imaging systems can be generated by combining Monte Carlo simulations and experimental measurements for commissioning imaging beams in the treatment planning. Conclusion: The current treatment planning systems are not yet equipped to perform patient specific dose calculations resulting from kV imaging procedures. The imaging dose from current kV image devices has been significantly reduced and is generally much less than that resulting from MV. Because the magnitude of kV imaging dose is significantly low and the variation between patients is modest, it is feasible to estimate dose based on imaging producers or protocols using tabulated values which provides an alternative to accomplish the task of accounting and reporting imaging doses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-PIS-Exhibit Hall-01: Tools for TG-142 Linac Imaging QA I

Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The therapy topic this year is solutions for TG-142 recommendations for linear accelerator imaging QA. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Automated Imaging QA for TG-142 with RIT Presentation Time: 2:45 – 3:15 PM This presentation will discuss software tools for automated imaging QA and phantom analysis for TG-142. All modalities used in radiation oncology will be discussed, including CBCT, planar kV imaging, planar MV imaging, and imaging and treatment coordinate coincidence. Vendor supplied phantoms as well as a variety of third-party phantoms will be shown, along with appropriate analyses, proper phantom setup procedures and scanning settings, and a discussion of image quality metrics. Tools for process automation will be discussed which include: RIT Cognition (machine learning for phantom image identification), RIT Cerberus (automated file system monitoring and searching), and RunQueueC (batch processing of multiple images). In addition to phantom analysis, tools for statistical tracking, trending, and reporting will be discussed. This discussion will include an introduction to statistical process control, a valuable tool in analyzing data and determining appropriate tolerances. An Introduction to TG-142 Imaging QA Using Standard Imaging Products Presentation Time: 3:15 – 3:45 PM Medical Physicists want to understand the logic behind TG-142 Imaging QA. What is often missing is a firm understanding of the connections between the EPID and OBI phantom imaging, the software “algorithms” that calculate the QA metrics, the establishment of baselines, and the analysis and interpretation of the results. The goal of our brief presentation will be to establish and solidify these connections. Our talk will be motivated by the Standard Imaging, Inc. phantom and software solutions. We will present and explain each of the image quality metrics in TG-142 in terms of the theory, mathematics, and algorithms used to implement them in the Standard Imaging PIPSpro software. In the process, we will identify the regions of phantom images that are analyzed by each algorithm. We then will discuss the process of the creation of baselines and typical ranges of acceptable values for each imaging quality metric.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

High resolution Cerenkov light imaging of induced positron distribution in proton therapy

Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, they conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a {sup 22}Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm{sup 3}) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The authors conclude that Cerenkov light imaging of proton-induced positron is promising for proton therapy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Monte Carlo simulation of PET and SPECT imaging of {sup 90}Y

Purpose: Yittrium-90 ({sup 90}Y) is traditionally thought of as a pure beta emitter, and is used in targeted radionuclide therapy, with imaging performed using bremsstrahlung single-photon emission computed tomography (SPECT). However, because {sup 90}Y also emits positrons through internal pair production with a very small branching ratio, positron emission tomography (PET) imaging is also available. Because of the insufficient image quality of {sup 90}Y bremsstrahlung SPECT, PET imaging has been suggested as an alternative. In this paper, the authors present the Monte Carlo-based simulation–reconstruction framework for {sup 90}Y to comprehensively analyze the PET and SPECT imaging techniques and to quantitatively consider the disadvantages associated with them. Methods: Our PET and SPECT simulation modules were developed using Monte Carlo simulation of Electrons and Photons (MCEP), developed by Dr. S. Uehara. PET code (MCEP-PET) generates a sinogram, and reconstructs the tomography image using a time-of-flight ordered subset expectation maximization (TOF-OSEM) algorithm with attenuation compensation. To evaluate MCEP-PET, simulated results of {sup 18}F PET imaging were compared with the experimental results. The results confirmed that MCEP-PET can simulate the experimental results very well. The SPECT code (MCEP-SPECT) models the collimator and NaI detector system, and generates the projection images and projection data. To save the computational time, the authors adopt the prerecorded {sup 90}Y bremsstrahlung photon data calculated by MCEP. The projection data are also reconstructed using the OSEM algorithm. The authors simulated PET and SPECT images of a water phantom containing six hot spheres filled with different concentrations of {sup 90}Y without background activity. The amount of activity was 163 MBq, with an acquisition time of 40 min. Results: The simulated {sup 90}Y-PET image accurately simulated the experimental results. PET image is visually superior to SPECT image because of the low background noise. The simulation reveals that the detected photon number in SPECT is comparable to that of PET, but the large fraction (approximately 75%) of scattered and penetration photons contaminates SPECT image. The lower limit of {sup 90}Y detection in SPECT image was approximately 200 kBq/ml, while that in PET image was approximately 100 kBq/ml. Conclusions: By comparing the background noise level and the image concentration profile of both the techniques, PET image quality was determined to be superior to that of bremsstrahlung SPECT. The developed simulation codes will be very useful in the future investigations of PET and bremsstrahlung SPECT imaging of {sup 90}Y.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2008

Hyperspectral Fluorescence and Reflectance Imaging Instrument

The system is a single hyperspectral imaging instrument that has the unique capability to acquire both fluorescence and reflectance high-spatial-resolution data that is inherently spatially and spectrally registered. Potential uses of this instrument include plant stress monitoring, counterfeit document detection, biomedical imaging, forensic imaging, and general materials identification. Until now, reflectance and fluorescence spectral imaging have been performed by separate instruments. Neither a reflectance spectral image nor a fluorescence spectral image alone yields as much information about a target surface as does a combination of the two modalities. Before this system was developed, to benefit from this combination, analysts needed to perform time-consuming post-processing efforts to co-register the reflective and fluorescence information. With this instrument, the inherent spatial and spectral registration of the reflectance and fluorescence images minimizes the need for this post-processing step. The main challenge for this technology is to detect the fluorescence signal in the presence of a much stronger reflectance signal. To meet this challenge, the instrument modulates artificial light sources from ultraviolet through the visible to the near-infrared part of the spectrum; in this way, both the reflective and fluorescence signals can be measured through differencing processes to optimize fluorescence and reflectance spectra as needed. The main functional components of the instrument are a hyperspectral imager, an illumination system, and an image-plane scanner. The hyperspectral imager is a one-dimensional (line) imaging spectrometer that includes a spectrally dispersive element and a two-dimensional focal plane detector array. The spectral range of the current imaging spectrometer is between 400 to 1,000 nm, and the wavelength resolution is approximately 3 nm. The illumination system consists of narrowband blue, ultraviolet, and other discrete wavelength light-emitting-diode (LED) sources and white-light LED sources designed to produce consistently spatially stable light. White LEDs provide illumination for the measurement of reflectance spectra, while narrowband blue and UV LEDs are used to excite fluorescence. Each spectral type of LED can be turned on or off depending on the specific remote-sensing process being performed. Uniformity of illumination is achieved by using an array of LEDs and/or an integrating sphere or other diffusing surface. The image plane scanner uses a fore optic with a field of view large enough to provide an entire scan line on the image plane. It builds up a two-dimensional image in pushbroom fashion as the target is scanned across the image plane either by moving the object or moving the fore optic. For fluorescence detection, spectral filtering of a narrowband light illumination source is sometimes necessary to minimize the interference of the source spectrum wings with the fluorescence signal. Spectral filtering is achieved with optical interference filters and absorption glasses. This dual spectral imaging capability will enable the optimization of reflective, fluorescence, and fused datasets as well as a cost-effective design for multispectral imaging solutions. This system has been used in plant stress detection studies and in currency analysis.

Ryan, Robert E.↗
NASA NTRS2011

Geometric registration of images by similarity transformation using two reference points

A method for registering a first image to a second image using a similarity transformation. The each image includes a plurality of pixels. The first image pixels are mapped to a set of first image coordinates and the second image pixels are mapped to a set of second image coordinates. The first image coordinates of two reference points in the first image are determined. The second image coordinates of these reference points in the second image are determined. A Cartesian translation of the set of second image coordinates is performed such that the second image coordinates of the first reference point match its first image coordinates. A similarity transformation of the translated set of second image coordinates is performed. This transformation scales and rotates the second image coordinates about the first reference point such that the second image coordinates of the second reference point match its first image coordinates.

Kang, Yong Q.↗
NASA NTRSDate not supplied

Imaging Science Requirements for a Uranus Flagship Mission

Introduction: Our presentation will summarize the requirements for UV/Visible/Near-IR remote-sensing imaging science instruments (including mapping spectrometers) envisioned for the Uranus Orbiter and Probe (UOP) mission recommended by the recent planetary decadal survey. The Uranus system offers many targets for imaging investigations. Imaging science investigations are crucial to answering fundamental questions about various physical processes that shape the Uranian system and drive its evolution. Each science objective addressed through imaging has requirements for observation and illumination geometries as well as coverage and resolution in the spatial, spectral and temporal dimensions. By combining the requirements for the diverse science targets in the Uranian system, we present a set of overarching imaging science requirements for UOP. Atmospheric Science: The study of Uranus’ atmosphere is crucial in understanding the planet's energy balance and interior heat flux. Imaging observations map how the atmosphere scatters incident solar radiation. Imaging is key to characterizing planetary-scale energy/material transport though global atmospheric dynamics and local meteorology. Hyperspectral mapping combined with radiative transfer analysis reveals the vertical distribution of clouds and hazes. Chronicling temporal variabilities of atmospheric features is key to understanding the various processes that operate within the dynamic Uranian atmosphere. A comprehensive understanding of Uranus' atmosphere is essential in deciphering the planet's origins and evolution as well as providing insight into the broader field of planetary and exoplanetary science. Magnetospheric Interactions: Imaging science is critical to understand the elusive Uranian aurorae. Mapping the aurorae and their temporal dynamics will reveal the interaction of Uranus’ complex magnetosphere with the solar wind. The apparent decades-long cooling of Uranus’ upper atmosphere is thought to be due to changes in energy input from the overlying magnetosphere, and so mapping and quantifying the auroral evidence for this energy flux is particularly relevant for upper atmospheric science In addition, Uranus’ large moons may generate auroral footprints, which can be used to constrain the planet’s unusual magnetic field structure. Satellite Interiors: Imaging science can address the potential habitability of the larger moons of Uranus by measuring their shapes and rotational states (including librations), which combined with gravity data are crucial to understanding their internal density structure. Satellite Origins: Origin markers such as organics and volatiles may be preserved on the satellite surfaces, which may be sensed by UV/IR mapping. Imaging combined with the moons’ densities may reveal whether the moons formed in Uranus’ circumplanetary disk, rings, or from ejecta of a giant impact on Uranus. Satellite Geology: Imaging investigations, including stereo imaging to obtain topography, will enable constraining each satellite’s geologic history by investigating the distributions and morphologies of impact craters, tectonic and potential cryovolcanic features, and regolith and mass wasting deposits. These records will help unravel the past complex history of orbital resonances that occurred between Uranian satellites, which may have driven geologic activity. Analyses of these features will also point to resurfacing styles and modification processes important for understanding each moon’s thermal evolution, and any present-day geological activity, including potential subsurface deep oceans or possible current activity. Additionally, hyperspectral imaging will enable mapping the surface composition and identifying the potential presence of material that may point to a subsurface ocean, such as ammonia-bearing species. Rings and Small Moons: Imaging observations elucidate the physical processes that contribute to the complex ring-moon system’s inferred unstable state. Imaging surveys will seek smaller moons and other debris that could provide evidence of past collisions, while precise astrometric data of moons will determine the current dynamical state of the system. Many of Uranus' rings are exceptionally narrow, and images of the rings covering a broad range of longitudes, and high-resolution images of features within the rings will reveal how these rings are confined and maintained, as well as illustrating the rings' internal structure and dynamics. Images of the rings and moons obtained at a variety of wavelengths and lighting conditions are also needed to quantify the composition and the size distribution of the small satellites and ring particles.

K M Sayanagi↗
DOE OSTI2013

A method for removing arm backscatter from EPID images

Purpose: To develop a method for removing the support arm backscatter from images acquired using current Varian electronic portal imaging devices (EPIDs).Methods: The effect of arm backscatter on EPID images was modeled using a kernel convolution method. The parameters of the model were optimized by comparing on-arm images to off-arm images. The model was used to develop a method to remove the effect of backscatter from measured EPID images. The performance of the backscatter removal method was tested by comparing backscatter corrected on-arm images to measured off-arm images for 17 rectangular fields of different sizes and locations on the imager. The method was also tested using on- and off-arm images from 42 intensity modulated radiotherapy (IMRT) fields.Results: Images generated by the backscatter removal method gave consistently better agreement with off-arm images than images without backscatter correction. For the 17 rectangular fields studied, the root mean square difference of in-plane profiles compared to off-arm profiles was reduced from 1.19% (standard deviation 0.59%) on average without backscatter removal to 0.38% (standard deviation 0.18%) when using the backscatter removal method. When comparing to the off-arm images from the 42 IMRT fields, the mean {gamma} and percentage of pixels with {gamma} < 1 were improved by the backscatter removal method in all but one of the images studied. The mean {gamma} value (1%, 1 mm) for the IMRT fields studied was reduced from 0.80 to 0.57 by using the backscatter removal method, while the mean {gamma} pass rate was increased from 72.2% to 84.6%.Conclusions: A backscatter removal method has been developed to estimate the image acquired by the EPID without any arm backscatter from an image acquired in the presence of arm backscatter. The method has been shown to produce consistently reliable results for a wide range of field sizes and jaw configurations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-J-159: Analysis of Total Imaging Uncertainty in Respiratory-Gated Radiotherapy

Purpose: In respiratory-gated radiotherapy, the gating phase during treatment delivery needs to coincide with the corresponding phase determined during the treatment plan. However, because radiotherapy is performed based on the image obtained for the treatment plan, the time delay, motion artifact, volume effect, and resolution in the images are uncertain. Thus, imaging uncertainty is the most basic factor that affects the localization accuracy. Therefore, these uncertainties should be analyzed. This study aims to analyze the total imaging uncertainty in respiratory-gated radiotherapy. Methods: Two factors of imaging uncertainties related to respiratory-gated radiotherapy were analyzed. First, CT image was used to determine the target volume and 4D treatment planning for the Varian Realtime Position Management (RPM) system. Second, an X-ray image was acquired for image-guided radiotherapy (IGRT) for the BrainLAB ExacTrac system. These factors were measured using a respiratory gating phantom. The conditions applied during phantom operation were as follows: respiratory wave form, sine curve; respiratory cycle, 4 s; phantom target motion amplitude, 10, 20, and 29 mm (which is maximum phantom longitudinal motion). The target and cylindrical marker implanted in the phantom coverage of the CT images was measured and compared with the theoretically calculated coverage from the phantom motion. The theoretical position of the cylindrical marker implanted in the phantom was compared with that acquired from the X-ray image. The total imaging uncertainty was analyzed from these two factors. Results: In the CT image, the uncertainty between the target and cylindrical marker’s actual coverage and the coverage of CT images was 1.19 mm and 2.50mm, respectively. In the Xray image, the uncertainty was 0.39 mm. The total imaging uncertainty from the two factors was 1.62mm. Conclusion: The total imaging uncertainty in respiratory-gated radiotherapy was clinically acceptable. However, an internal margin should be added to account for the total imaging uncertainty.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-A-BRF-11: Image Intensity Non-Uniformities Between MRI Simulation and Diagnostic MRI

Purpose: MRI simulation for MRI-based radiotherapy demands that patients be setup in treatment position, which frequently involves use of alternative radiofrequency (RF) coil configurations to accommodate immobilized patients. However, alternative RF coil geometries may exacerbate image intensity non-uniformities (IINU) beyond those observed in diagnostic MRI, which may challenge image segmentation and registration accuracy as well as confound studies assessing radiotherapy response when MR simulation images are used as baselines for evaluation. The goal of this work was to determine whether differences in IINU exist between MR simulation and diagnostic MR images. Methods: ACR-MRI phantom images were acquired at 3T using a spin-echo sequence (TE/TR:20/500ms, rBW:62.5kHz, TH/skip:5/5mm). MR simulation images were obtained by wrapping two flexible phased-array RF coils around the phantom. Diagnostic MR images were obtained by placing the phantom into a commercial phased-array head coil. Pre-scan normalization was enabled in both cases. Images were transferred offline and corrected for IINU using the MNI N3 algorithm. Coefficients of variation (CV=σ/μ) were calculated for each slice. Wilcoxon matched-pairs and Mann-Whitney tests compared CV values between original and N3 images and between MR simulation and diagnostic MR images. Results: Significant differences in CV were detected between original and N3 images in both MRI simulation and diagnostic MRI groups (p=0.010, p=0.010). In addition, significant differences in CV were detected between original MR simulation and original and N3 diagnostic MR images (p=0.0256, p=0.0016). However, no significant differences in CV were detected between N3 MR simulation images and original or N3 diagnostic MR images, demonstrating the importance of correcting MR simulation images beyond pre-scan normalization prior to use in radiotherapy. Conclusions: Alternative RF coil configurations used in MRI simulation can Result in significant IINU differences compared to diagnostic MR images. The MNI N3 algorithm reduced MR simulation IINU to levels observed in diagnostic MR images. Funding provided by Advancing a Healthier Wisconsin.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

Purpose: Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. Methods: kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. Results: Regular dual-energy imaging was able to increase tracking accuracy in left–right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. Conclusions: This study has highlighted the influence of patient anatomy on the success rate of real-time markerless tumor tracking using dual-energy imaging. Additionally, the importance of the spectral separation of the imaging beams used to generate the dual-energy images has been shown.

60 APPLIED LIFE SCIENCES↗