Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Imaging”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TU-G-204-04: A Unified Strategy for Bi-Factorial Optimization of Radiation Dose and Contrast Dose in CT Imaging

Purpose: To substantiate the interdependency of contrast dose, radiation dose, and image quality in CT towards the patient- specific optimization of the imaging protocols Methods: The study deployed two phantom platforms. A variable sized (12, 18, 23, 30, 37 cm) phantom (Mercury-3.0) containing an iodinated insert (8.5 mgI/ml) was imaged on a representative CT scanner at multiple CTDI values (0.7–22.6 mGy). The contrast and noise were measured from the reconstructed images for each phantom diameter. Linearly related to iodine-concentration, contrast-to-noise ratio (CNR), were calculated for 16 iodine-concentration levels (0–8.5 mgI/ml). The analysis was extended to a recently developed suit of 58 virtual human models (5D XCAT) with added contrast dynamics. Emulating a contrast-enhanced abdominal image procedure and targeting a peak-enhancement in aorta, each XCAT phantom was “imaged” using a simulation platform (CatSim, GE). 3D surfaces for each patient/size established the relationship between iodine-concentration, dose, and CNR. The ratios of change in iodine-concentration versus dose (IDR) to yield a constant change in CNR were calculated for each patient size. Results: Mercury phantom results show the image-quality size- dependence on CTDI and IC levels. For desired image-quality values, the iso-contour-lines reflect the trade off between contrast-material and radiation doses. For a fixed iodine-concentration (4 mgI/mL), the IDR values for low (1.4 mGy) and high (11.5 mGy) dose levels were 1.02, 1.07, 1.19, 1.65, 1.54, and 3.14, 3.12, 3.52, 3.76, 4.06, respectively across five sizes. The simulation data from XCAT models confirmed the empirical results from Mercury phantom. Conclusion: The iodine-concentration, image quality, and radiation dose are interdependent. The understanding of the relationships between iodine-concentration, image quality, and radiation dose will allow for a more comprehensive optimization of CT imaging devices and techniques, providing the methodology to balance iodine-concentration and dose based on patient’s attributes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

The SRT reconstruction algorithm for semiquantification in PET imaging

Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT exhibits higher contrast and lower bias than OSEM at the cold lesions. This improvement is achieved at the expense of increasing the noise in the reconstructed images. For the hot lesions, SRT exhibits a small improvement in contrast and LBR over OSEM with 21 subsets and two iterations; however, this improvement is not statistically significant. As the number of iterations increases, the performance of OSEM improves over SRT but again without statistical significance. The curves of contrast and LBR as a function of IR after Gaussian blurring indicate that the advantage of SRT in the cold regions is maintained even after decreasing the noise level by Gaussian blurring. Conclusions: SRT, at the expense of slightly increased noise in the reconstructed images, reconstructs images of higher contrast and lower bias than the clinical protocol of OSEM. This improvement is particularly evident for images involving cold regions. Thus, it appears that SRT should be particularly useful for the quantification of low-count and cold regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Scatter and crosstalk corrections for {sup 99m}Tc/{sup 123}I dual-radionuclide imaging using a CZT SPECT system with pinhole collimators

Purpose: The energy spectrum for a cadmium zinc telluride (CZT) detector has a low energy tail due to incomplete charge collection and intercrystal scattering. Due to these solid-state detector effects, scatter would be overestimated if the conventional triple-energy window (TEW) method is used for scatter and crosstalk corrections in CZT-based imaging systems. The objective of this work is to develop a scatter and crosstalk correction method for {sup 99m}Tc/{sup 123}I dual-radionuclide imaging for a CZT-based dedicated cardiac SPECT system with pinhole collimators (GE Discovery NM 530c/570c). Methods: A tailing model was developed to account for the low energy tail effects of the CZT detector. The parameters of the model were obtained using {sup 99m}Tc and {sup 123}I point source measurements. A scatter model was defined to characterize the relationship between down-scatter and self-scatter projections. The parameters for this model were obtained from Monte Carlo simulation using SIMIND. The tailing and scatter models were further incorporated into a projection count model, and the primary and self-scatter projections of each radionuclide were determined with a maximum likelihood expectation maximization (MLEM) iterative estimation approach. The extracted scatter and crosstalk projections were then incorporated into MLEM image reconstruction as an additive term in forward projection to obtain scatter- and crosstalk-corrected images. The proposed method was validated using Monte Carlo simulation, line source experiment, anthropomorphic torso phantom studies, and patient studies. The performance of the proposed method was also compared to that obtained with the conventional TEW method. Results: Monte Carlo simulations and line source experiment demonstrated that the TEW method overestimated scatter while their proposed method provided more accurate scatter estimation by considering the low energy tail effect. In the phantom study, improved defect contrasts were observed with both correction methods compared to no correction, especially for the images of {sup 99m}Tc in dual-radionuclide imaging where there is heavy contamination from {sup 123}I. In this case, the nontransmural defect contrast was improved from 0.39 to 0.47 with the TEW method and to 0.51 with their proposed method and the transmural defect contrast was improved from 0.62 to 0.74 with the TEW method and to 0.73 with their proposed method. In the patient study, the proposed method provided higher myocardium-to-blood pool contrast than that of the TEW method. Similar to the phantom experiment, the improvement was the most substantial for the images of {sup 99m}Tc in dual-radionuclide imaging. In this case, the myocardium-to-blood pool ratio was improved from 7.0 to 38.3 with the TEW method and to 63.6 with their proposed method. Compared to the TEW method, the proposed method also provided higher count levels in the reconstructed images in both phantom and patient studies, indicating reduced overestimation of scatter. Using the proposed method, consistent reconstruction results were obtained for both single-radionuclide data with scatter correction and dual-radionuclide data with scatter and crosstalk corrections, in both phantom and human studies. Conclusions: The authors demonstrate that the TEW method leads to overestimation in scatter and crosstalk for the CZT-based imaging system while the proposed scatter and crosstalk correction method can provide more accurate self-scatter and down-scatter estimations for quantitative single-radionuclide and dual-radionuclide imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-34: Automatic Target-Based Patient Positioning Framework for Image-Guided Radiotherapy in Prostate Cancer Treatment

Purpose: Current image-guided radiotherapy (IGRT) procedure is bonebased patient positioning, followed by subjective manual correction using cone beam computed tomography (CBCT). This procedure might cause the misalignment of the patient positioning. Automatic target-based patient positioning systems achieve the better reproducibility of patient setup. Our aim of this study was to develop an automatic target-based patient positioning framework for IGRT with CBCT images in prostate cancer treatment. Methods: Seventy-three CBCT images of 10 patients and 24 planning CT images with digital imaging and communications in medicine for radiotherapy (DICOM-RT) structures were used for this study. Our proposed framework started from the generation of probabilistic atlases of bone and prostate from 24 planning CT images and prostate contours, which were made in the treatment planning. Next, the gray-scale histograms of CBCT values within CTV regions in the planning CT images were obtained as the occurrence probability of the CBCT values. Then, CBCT images were registered to the atlases using a rigid registration with mutual information. Finally, prostate regions were estimated by applying the Bayesian inference to CBCT images with the probabilistic atlases and CBCT value occurrence probability. The proposed framework was evaluated by calculating the Euclidean distance of errors between two centroids of prostate regions determined by our method and ground truths of manual delineations by a radiation oncologist and a medical physicist on CBCT images for 10 patients. Results: The average Euclidean distance between the centroids of extracted prostate regions determined by our proposed method and ground truths was 4.4 mm. The average errors for each direction were 1.8 mm in anteroposterior direction, 0.6 mm in lateral direction and 2.1 mm in craniocaudal direction. Conclusion: Our proposed framework based on probabilistic atlases and Bayesian inference might be feasible to automatically determine prostate regions on CBCT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Time-resolved detectors for quantum ghost imaging

Quantum ghost imaging is a method that utilizes the correlated detection of two photons to generate an image. One photon is detected by an imaging sensor and the other by a single-element bucket detector. The selection of the imaging sensor and its capabilities relative to the bucket detector impact the quality of the ghost images. This work examines a SPAD array and a photocathode detector as imaging sensors for quantum ghost imaging. We discuss how to achieve optimal images using these two technologies. We also demonstrate that these devices are able to generate ghost images at 1Hz frame rates, expanding the technique to biologically relevant time scales.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting

Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method through the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.

14 SOLAR ENERGY↗
DOE OSTI2013

Cone Beam Computed Tomography Image Guidance System for a Dedicated Intracranial Radiosurgery Treatment Unit

Purpose: Image guidance has improved the precision of fractionated radiation treatment delivery on linear accelerators. Precise radiation delivery is particularly critical when high doses are delivered to complex shapes with steep dose gradients near critical structures, as is the case for intracranial radiosurgery. To reduce potential geometric uncertainties, a cone beam computed tomography (CT) image guidance system was developed in-house to generate high-resolution images of the head at the time of treatment, using a dedicated radiosurgery unit. The performance and initial clinical use of this imaging system are described. Methods and Materials: A kilovoltage cone beam CT system was integrated with a Leksell Gamma Knife Perfexion radiosurgery unit. The X-ray tube and flat-panel detector are mounted on a translational arm, which is parked above the treatment unit when not in use. Upon descent, a rotational axis provides 210 Degree-Sign of rotation for cone beam CT scans. Mechanical integrity of the system was evaluated over a 6-month period. Subsequent clinical commissioning included end-to-end testing of targeting performance and subjective image quality performance in phantoms. The system has been used to image 2 patients, 1 of whom received single-fraction radiosurgery and 1 who received 3 fractions, using a relocatable head frame. Results: Images of phantoms demonstrated soft tissue contrast visibility and submillimeter spatial resolution. A contrast difference of 35 HU was easily detected at a calibration dose of 1.2 cGy (center of head phantom). The shape of the mechanical flex vs scan angle was highly reproducible and exhibited <0.2 mm peak-to-peak variation. With a 0.5-mm voxel pitch, the maximum targeting error was 0.4 mm. Images of 2 patients were analyzed offline and submillimeter agreement was confirmed with conventional frame. Conclusions: A cone beam CT image guidance system was successfully adapted to a radiosurgery unit. The system is capable of producing high-resolution images of bone and soft tissue. The system is in clinical use and provides excellent image guidance without invasive frames.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Megavoltage Computed Tomography Image Guidance With Helical Tomotherapy in Patients With Vertebral Tumors: Analysis of Factors Influencing Interobserver Variability

Purpose: To evaluate megavoltage computed tomography (MVCT)-based image guidance with helical tomotherapy in patients with vertebral tumors by analyzing factors influencing interobserver variability, considered as quality criterion of image guidance. Methods and Materials: Five radiation oncologists retrospectively registered 103 MVCTs in 10 patients to planning kilovoltage CTs by rigid transformations in 4 df. Interobserver variabilities were quantified using the standard deviations (SDs) of the distributions of the correction vector components about the observers' fraction mean. To assess intraobserver variabilities, registrations were repeated after {>=}4 weeks. Residual deviations after setup correction due to uncorrectable rotational errors and elastic deformations were determined at 3 craniocaudal target positions. To differentiate observer-related variations in minimizing these residual deviations across the 3-dimensional MVCT from image resolution effects, 2-dimensional registrations were performed in 30 single transverse and sagittal MVCT slices. Axial and longitudinal MVCT image resolutions were quantified. For comparison, image resolution of kilovoltage cone-beam CTs (CBCTs) and interobserver variability in registrations of 43 CBCTs were determined. Results: Axial MVCT image resolution is 3.9 lp/cm. Longitudinal MVCT resolution amounts to 6.3 mm, assessed as full-width at half-maximum of thin objects in MVCTs with finest pitch. Longitudinal CBCT resolution is better (full-width at half-maximum, 2.5 mm for CBCTs with 1-mm slices). In MVCT registrations, interobserver variability in the craniocaudal direction (SD 1.23 mm) is significantly larger than in the lateral and ventrodorsal directions (SD 0.84 and 0.91 mm, respectively) and significantly larger compared with CBCT alignments (SD 1.04 mm). Intraobserver variabilities are significantly smaller than corresponding interobserver variabilities (variance ratio [VR] 1.8-3.1). Compared with 3-dimensional registrations, 2-dimensional registrations have significantly smaller interobserver variability in the lateral and ventrodorsal directions (VR 3.8 and 2.8, respectively) but not in the craniocaudal direction (VR 0.75). Conclusion: Tomotherapy image guidance precision is affected by image resolution and residual deviations after setup correction. Eliminating the effect of residual deviations yields small interobserver variabilities with submillimeter precision in the axial plane. In contrast, interobserver variability in the craniocaudal direction is dominated by the poorer longitudinal MVCT image resolution. Residual deviations after image guidance exist and need to be considered when dose gradients ultimately achievable with image guided radiation therapy techniques are analyzed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

High-speed adaptive contact-mode atomic force microscopy imaging with near-minimum-force

In this paper, an adaptive contact-mode imaging approach is proposed to replace the traditional contact-mode imaging by addressing the major concerns in both the speed and the force exerted to the sample. The speed of the traditional contact-mode imaging is largely limited by the need to maintain precision tracking of the sample topography over the entire imaged sample surface, while large image distortion and excessive probe-sample interaction force occur during high-speed imaging. In this work, first, the image distortion caused by the topography tracking error is accounted for in the topography quantification. Second, the quantified sample topography is utilized in a gradient-based optimization method to adjust the cantilever deflection set-point for each scanline closely around the minimal level needed for maintaining stable probe-sample contact, and a data-driven iterative feedforward control that utilizes a prediction of the next-line topography is integrated to the topography feeedback loop to enhance the sample topography tracking. The proposed approach is demonstrated and evaluated through imaging a calibration sample of square pitches at both high speeds (e.g., scan rate of 75 Hz and 130 Hz) and large sizes (e.g., scan size of 30 μm and 80 μm). The experimental results show that compared to the traditional constant-force contact-mode imaging, the imaging speed can be increased by over 30 folds (with the scanning speed at 13 mm/s), and the probe-sample interaction force can be reduced by more than 15% while maintaining the same image quality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Neural network denoising of x-ray images from high-energy-density experiments

Noise is a consistent problem for x-ray transmission images of High-Energy-Density (HED) experiments because it can significantly affect the accuracy of inferring quantitative physical properties from these images. We consider experiments that use x-ray area backlighting to image a thin layer of opaque material within a physics package to observe its hydrodynamic evolution. The spatial variance of the x-ray transmission across the system due to changing opacity serves as an analog for measuring density in this evolving layer. The noise in these images adds nonphysical variations in measured intensity, which can significantly reduce the accuracy of our inferred densities, particularly at small spatial scales. Denoising these images is thus necessary to improve our quantitative analysis, but any denoising method also affects the underlying information in the image. In this paper, we present a method for denoising HED x-ray images via a deep convolutional neural network model with a modified DenseNet architecture. In our denoising framework, we estimate the noise present in the real (data) images of interest and apply the inferred noise distribution to a set of natural images. These synthetic noisy images are then used to train a neural network model to recognize and remove noise of that character. We show that our trained denoiser network significantly reduces the noise in our experimental images while retaining important physical features.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Gravitational lensing and ghost images in the regular Bardeen no-horizon spacetimes

We study deflection of light rays and gravitational lensing in the regular Bardeen no-horizon spacetimes. Flatness of these spacetimes in the central region implies existence of interesting optical effects related to photons crossing the gravitational field of the no-horizon spacetimes with low impact parameters. These effects occur due to existence of a critical impact parameter giving maximal deflection of light rays in the Bardeen no-horizon spacetimes. We give the critical impact parameter in dependence on the specific charge of the spacetimes, and discuss 'ghost' direct and indirect images of Keplerian discs, generated by photons with low impact parameters. The ghost direct images can occur only for large inclination angles of distant observers, while ghost indirect images can occur also for small inclination angles. We determine the range of the frequency shift of photons generating the ghost images and determine distribution of the frequency shift across these images. We compare them to those of the standard direct images of the Keplerian discs. The difference of the ranges of the frequency shift on the ghost and direct images could serve as a quantitative measure of the Bardeen no-horizon spacetimes. The regions of the Keplerian discs giving the ghost images are determined in dependence on the specific charge of the no-horizon spacetimes. For comparison we construct direct and indirect (ordinary and ghost) images of Keplerian discs around Reissner-Nördström naked singularities demonstrating a clear qualitative difference to the ghost direct images in the regular Bardeen no-horizon spacetimes. The optical effects related to the low impact parameter photons thus give clear signature of the regular Bardeen no-horizon spacetimes, as no similar phenomena could occur in the black hole or naked singularity spacetimes. Similar direct ghost images have to occur in any regular no-horizon spacetimes having nearly flat central region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Simultaneous and Constrained Calibration of Multiple Hyperspectral Images Through a New Generalized Empirical Line Model

The empirical line (EL) calibration method is commonly used for atmospheric correction of remotely sensed spectral images and recovery of surface reflectance. The current EL-based methods are applicable to calibrate only single images. Therefore, the use of the EL calibration is impractical for imaging campaigns, where many (partially overlapped) images are acquired to cover a large area. In addition, the EL results are unconstrained and an undesired reflectance with negative values or larger than 100% can be obtained. In this paper, we use the standard EL model to formulate a new generalized empirical line (GEL) model. Based on the GEL, we present a novel method for simultaneous and constrained calibration of multiple images. This new method allows for calibration through multiple image constrained empirical line (MIcEL) and three additional calibration modes. Given a set of images, we use the available ground targets and automatically extracted tie points between overlapping images to calibrate all the images in the set simultaneously. Quantitative and visual assessments of the proposed method were carried out relatively to the off-the-shelf method quick atmospheric correction (QUAC), using real hyperspectral images and field measurements. The results clearly show the superiority of MIcEL with respect to the minimization of the difference between the reflectance values of the same object in different overlapping images. An assessment of the absolute accuracy, with respect to 11 field measurement points, shows that the accuracy of MIcEL, with an average mean absolute error (MAE) of ~11%, is comparable with respect to the QUAC.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Adaptive Visual Sort and Summary of Micrographic Images of Nanoparticles for Forensic Analysis

Forensic analysis of nanoparticles is often conducted through the collection and identifi- cation of electron microscopy images to determine the origin of suspected nuclear material. Each image is carefully studied by experts for classification of materials based on texture, shape, and size. Manually inspecting large image datasets takes enormous amounts of time. However, automatic classification of large image datasets is a challenging problem due to the complexity involved in choosing image features, the lack of training data available for effective machine learning methods, and the availability of user interfaces to parse through images. Therefore, a significant need exists for automated and semi-automated methods to help analysts perform accurate image classification in large image datasets. We present INStINCt, our Intelligent Signature Canvas, as a framework for quickly organizing image data in a web based canvas framework. Images are partitioned using small sets of example images, chosen by users, and presented in an optimal layout based on features derived from convolutional neural networks.

active canvas↗
DOE OSTI2013

The need for application-based adaptation of deformable image registration

Purpose: To utilize a deformable phantom to objectively evaluate the accuracy of 11 different deformable image registration (DIR) algorithms. Methods: The phantom represents an axial plane of the pelvic anatomy. Urethane plastic serves as the bony anatomy and urethane rubber with three levels of Hounsfield units (HU) is used to represent fat and organs, including the prostate. A plastic insert is placed into the phantom to simulate bladder filling. Nonradiopaque markers reside on the phantom surface. Optical camera images of these markers are used to measure the positions and determine the deformation from the bladder insert. Eleven different DIR algorithms are applied to the full and empty-bladder computed tomography images of the phantom (fixed and moving volumes, respectively) to calculate the deformation. The algorithms include those from MIM Software (MIM) and Velocity Medical Solutions (VEL) and nine different implementations from the deformable image registration and adaptive radiotherapy toolbox for Matlab. These algorithms warp one image to make it similar to another, but must utilize a method for regularization to avoid physically unrealistic deformation scenarios. The mean absolute difference (MAD) between the HUs at the marker locations on one image and the calculated location on the other serves as a metric to evaluate the balance between image similarity and regularization. To demonstrate the effect of regularization on registration accuracy, an additional beta version of MIM was created with a variable smoothness factor that controls the emphasis of the algorithm on regularization. The distance to agreement between the measured and calculated marker deformations is used to compare the overall spatial accuracy of the DIR algorithms. This overall spatial accuracy is also utilized to evaluate the phantom geometry and the ability of the phantom soft-tissue heterogeneity to represent patient data. To evaluate the ability of the DIR algorithms to accurately transfer anatomical contours, the rectum is delineated on both the fixed and moving images. A Dice similarity coefficient is then calculated between the contour on the fixed image and that transferred, via the calculated deformation, from the moving to the fixed image. Results: The phantom possesses sufficient soft-tissue heterogeneity to act as a proxy for patient data. Large discrepancies appear between the algorithms and the measured ground-truth deformation. VEL yields the smallest mean spatial error and a Dice coefficient of 0.90. MIM produces the lowest MAD value and the highest Dice coefficient of 0.96, but creates the largest spatial errors. Increasing the MIM smoothness factor above the default value improves the overall spatial accuracy, but the factor associated with the lowest mean error decreases the Dice coefficient to 0.85. Conclusions: Different applications of DIR require disparate balances between image similarity and regularization. A DIR algorithm that is optimized only for its ability to transfer anatomical contours will yield large deformation errors in homogeneous regions, which is problematic for dose mapping. For this reason, these algorithms must be tested for their overall spatial accuracy. The developed phantom is an objective tool for this purpose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-66: Radiomics and Image Registration Updates for the Computational Environment for Radiotherapy Research (CERR)

Purpose: To present new tools in CERR for Radiomics, image registration and other software updates and additions. Methods: Radiomics: CERR supports generating 3-D texture metrics based on gray scale co-occurance. Two new ways to calculate texture features were added: (1) Local Texture Averaging: Local texture is calculated around a voxel within the userdefined bounding box. The final texture metrics are the average of local textures for all the voxels. This is useful to detect any local texture patterns within an image. (2) Image Smoothing: A convolution ball of user-defined radius is rolled over an image to smooth out artifacts. The texture metrics are then computed on the smooth image. Image Registration: (1) Support was added to import deformation vector fields as well as non-deformable transformation matrices generated by vendor software and stored in standard DICOM format. (2) Support was added to use image within masks while computing image deformations. CT to MR registration is supported. This registration uses morphological edge information within the images to guide the deformation process. In addition to these features, other noteworthy additions to CERR include (1) Irregularly shaped ROI: This is done by taking intersection between infinitely extended irregular polygons drawn on any of the two views. Such an ROI is more conformal and useful in avoiding any unwanted parts of images that cannot be avoided with the conventional cubic box. The ROI is useful to generate Radiomics metrics. (2) Ability to insert RTDOSE in DICOM format to existing CERR plans. (3) Ability to import multi-frame PET-CT and SPECT-CT while maintaining spatial registration between the two modalities. (4) Ability to compile CERR on Unix-like systems. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics, Image-Registration and Outcomes modeling.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

SU-E-I-68: Practical Considerations On Implementation of the Image Gently Pediatric CT Protocols

Purpose: One limitation associated with the Image Gently pediatric CT protocols is practical implementation of the recommended manual techniques. Inconsistency as a result of different practice is a possibility among technologist. An additional concern is the added risk of data error that would result in over or underexposure. The Automatic Exposure Control (AEC) features automatically reduce radiation for children. However, they do not work efficiently for the patients of very small size and relative large size. This study aims to implement the Image Gently pediatric CT protocols in the practical setting while maintaining the use of AEC features for pediatric patients of varying size. Methods: Anthropomorphological abdomen phantoms were scanned in a CT scanner using the Image Gently pediatric protocols, the AEC technique with a fixed adult baseline, and automatic protocols with various baselines. The baselines were adjusted corresponding to patient age, weight and posterioranterior thickness to match the Image Gently pediatric CT manual techniques. CTDIvol was recorded for each examination. Image noise was measured and recorded for image quality comparison. Clinical images were evaluated by pediatric radiologists. Results: By adjusting vendor default baselines used in the automatic techniques, radiation dose and image quality can match those of the Image Gently manual techniques. In practice, this can be achieved by dividing pediatric patients into three major groups for technologist reference: infant, small child, and large child. Further division can be done but will increase the number of CT protocols. For each group, AEC can efficiently adjust acquisition techniques for children. This implementation significantly overcomes the limitation of the Image Gently manual techniques. Conclusion: Considering the effectiveness in clinical practice, Image Gently Pediatric CT protocols can be implemented in accordance with AEC techniques, with adjusted baselines, to achieve the goal of providing the most appropriate radiation dose for pediatric patients of varying sizes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-88: Mammography Imaging: Does Positioning Matter?

Purpose: In mammography, compression is imperative for quality images and glandular radiation exposure dose. The thickness of the compressed breast directly determines mammography acquisition parameters. The compressed thickness varies due to variation in technologist practice, even for the same patient imaged at different time. This study is to investigate potential effect of the variation in breast positioning on radiation dose and image quality. Methods: Radiation dose at different thicknesses was measured with a BR-12 breast phantom for both conventional craniocaudal view and tomosynthesis in a Hologic Tomosynthesis mammography system. The CIRS stereotactic needle biopsy training phantom embedded dense masses and microcalcification in various sizes were imaged for image quality evaluation. Radiologists evaluated images. Clinical mammograms from the same patient but acquired at different time were retrospectively retrieved to evaluate potential effects of variation in positioning. Results: Acquisition parameters (kVp and mAs) increase with the increased phantom thickness. Radiation exposure increases following an exponential trend. The stereotactic phantom images showed loss of spatial and contrast resolution with inappropriate positioning. The compressed pressure may not be a good indicator for appropriate positioning. The inclusion of different amount of pectoralis muscle may lead to the same compressed pressure but different compressed thickness. The initial retrospective study of 3 patients showed that there were potential large variations in positioning the same patient at different examination time, resulting in large variations in patient radiation dose and image quality. Conclusion: Variations in patient positioning potentially influence patient radiation dose and image quality. The technologist has the critical responsibility to position patient to provide quality images in spite of different breast and body types. To reduce intra and inter practice variations in positioning patient, a training program among each breast imaging center may be a need.

60 APPLIED LIFE SCIENCES↗