Efficient Local Statistical Analysis via Point-Wise Histograms in Tetrahedral Meshes and Curvilinear Grids
Not provided.
Computer Science↗
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SU-F-T-254: Dose Volume Histogram (DVH) Analysis of Breath Hold Vs Free Breathing Techniques for Esophageal Tumors
Purpose: Lung and heart doses and associated toxicity are of concern in radiotherapy for esophageal cancer. This study evaluates the dosimetry of deep-inspiration-breath-hold (DIBH) technique as compared to freebreathing( FB) using 3D-conformal treatment(3D-CRT) of esophageal cancer. Methods: Eight patients were planned with FB and DIBH CT scans. DIBH scans were acquired using Varian RPM system. FB and DIBH CTs were contoured per RTOG-1010 to create the planning target volume(PTV) as well as organs at risk volumes(OAR). Two sets of gross target volumes(GTV) with 5cm length were contoured for each patient: proximal at the level of the carina and distal at the level of gastroesophageal junction and were enlarged with appropriate margin to generate Clinical Target Volume and PTV. 3D-CRT plans were created on Eclipse planning system for 45Gy to cover 95% of PTV in 25 fractions for both proximal and distal tumors on FB and DIBH scans. For distal tumors celiac nodes were covered electively. DVH parameters for lung and heart OARs were generated and analyzed. Results: All DIBH DVH parameters were normalized to FB plan values. Average of heart-mean and heart-V40 was 0.70 and 0.66 for proximal lesions. For distal lesions ratios were 1.21 and 2.22 respectively. For DIBH total lung volume increased by 2.43 times versus FB scan. Average of lung-mean, V30, V20, V10, V5 are 0.82, 0.92, 0.76, 0.77 and 0.79 for proximal lesions and 1.17,0.66,0.87,0.93 and 1.03 for distal lesions. Heart doses were lower for breath-hold proximal lesions but higher for distal lesions as compared to free-breathing plans. Lung doses were lower for both proximal and distal breath-hold lesions except mean lung dose and V5 for distal lesions. Conclusion: This study showed improvement of OAR doses for esophageal lesions at mid-thoracic level utilizing DIBH vs FB technique but did not show consistent OAR sparing with DIBH for distal lesions.
60 APPLIED LIFE SCIENCES↗
SU-F-T-340: Direct Editing of Dose Volume Histograms: Algorithms and a Unified Convex Formulation for Treatment Planning with Dose Constraints
Purpose: To develop a procedure for including dose constraints in convex programming-based approaches to treatment planning, and to support dynamic modification of such constraints during planning. Methods: We present a mathematical approach that allows mean dose, maximum dose, minimum dose and dose volume (i.e., percentile) constraints to be appended to any convex formulation of an inverse planning problem. The first three constraint types are convex and readily incorporated. Dose volume constraints are not convex, however, so we introduce a convex restriction that is related to CVaR-based approaches previously proposed in the literature. To compensate for the conservatism of this restriction, we propose a new two-pass algorithm that solves the restricted problem on a first pass and uses this solution to form exact constraints on a second pass. In another variant, we introduce slack variables for each dose constraint to prevent the problem from becoming infeasible when the user specifies an incompatible set of constraints. We implement the proposed methods in Python using the convex programming package cvxpy in conjunction with the open source convex solvers SCS and ECOS. Results: We show, for several cases taken from the clinic, that our proposed method meets specified constraints (often with margin) when they are feasible. Constraints are met exactly when we use the two-pass method, and infeasible constraints are replaced with the nearest feasible constraint when slacks are used. Finally, we introduce ConRad, a Python-embedded free software package for convex radiation therapy planning. ConRad implements the methods described above and offers a simple interface for specifying prescriptions and dose constraints. Conclusion: This work demonstrates the feasibility of using modifiable dose constraints in a convex formulation, making it practical to guide the treatment planning process with interactively specified dose constraints. This work was supported by the Stanford BioX Graduate Fellowship and NIH Grant 5R01CA176553.
60 APPLIED LIFE SCIENCES↗
SHIVER - Spectroscopy HIstogram Visualizer for Event Reduction
Visualizing data from neutron scattering experiments is the first step in understanding the physics. The program is intended to generate and plot cuts and slices, through the four dimensional single crystal inelastic datasets, measured on direct geometry neutron spectrometers at the Spallation Neutron Source (ARCS, CNCS, HYSPEC, SEQUOIA).
Savici, AndreiT [Oak Ridge National Laboratory (OR↗
Method of characterizing residual stress in ferromagnetic materials using a pulse histogram of acoustic emission signals
The invention is a method and apparatus for characterizing residual uniaxial stress in a ferromagnetic test member by distinguishing between residual stresses resulting from positive (tension) forces and negative (compression) forces by using the distinct and known magnetoacoustic (MAC) and a magnetoacoustic emission (MAE) measurement circuit means. A switch permits the selective operation of the respective circuit means.
Namkung, Min↗
A histogram-based technique for rapid vector extraction from PIV photographs
A new analysis technique, performed totally in the image plane, is proposed which rapidly extracts all available vectors from individual interrogation regions on PIV photographs. The technique avoids the need for using Fourier transforms with the associated computational burden. The data acquisition and analysis procedure is described, and results of a preliminary simulation study to evaluate the accuracy of the technique are presented. Recently obtained PIV photographs are analyzed.
Humphreys, William M., Jr.↗
Assignment 1: Histogram, Descriptive Statistics, and Scatter Plots
No abstract available
Newman, Jessica A.↗
Gamma ray spectroscopy employing divalent europium-doped alkaline earth halides and digital readout for accurate histogramming
According to one embodiment, a scintillator radiation detector system includes a scintillator, and a processing device for processing pulse traces corresponding to light pulses from the scintillator, where the processing device is configured to: process each pulse trace over at least two temporal windows and to use pulse digitization to improve energy resolution of the system. According to another embodiment, a scintillator radiation detector system includes a processing device configured to: fit digitized scintillation waveforms to an algorithm, perform a direct integration of fit parameters, process multiple integration windows for each digitized scintillation waveform to determine a correction factor, and apply the correction factor to each digitized scintillation waveform.
36 MATERIALS SCIENCE↗
A Formula for the Maximum Number of Bins for Approximately Smooth Histograms with Application to the Pearson Chi2 Test and Related Topics.
Abstract not provided.
Dalbey, Keith↗
Boundary detection evaluation
Illustrative embodiments are directed to a method and apparatus for evaluating boundary detection in an image. A processed image is received, wherein a detected boundary of an image of an object is identified in the processed image. A Radon transform is applied to the processed image for a plurality of angles to form a processed image histogram corresponding to the detected boundary for each of the plurality of angles. The processed image histogram for each of the plurality of angles and a corresponding ground truth histogram for each of the plurality of angles is normalized to provide a normalized processed image histogram and a normalized ground truth histogram for each of the plurality of angles, wherein the ground truth histogram corresponds to a ground truth boundary of the object for a corresponding angle. An indication of the edges of the normalized processed image histogram for each of the plurality of angles is plotted to form a boundary detection evaluation visualization.
Wantuch, Andrew C.↗
Boundary detection evaluation
Illustrative embodiments are directed to a method and apparatus for evaluating boundary detection in an image. A processed image is received, wherein a detected boundary of an image of an object is identified in the processed image. A Radon transform is applied to the processed image for a plurality of angles to form a processed image histogram corresponding to the detected boundary for each of the plurality of angles. The processed image histogram for each of the plurality of angles and a corresponding ground truth histogram for each of the plurality of angles is normalized to provide a normalized processed image histogram and a normalized ground truth histogram for each of the plurality of angles, wherein the ground truth histogram corresponds to a ground truth boundary of the object for a corresponding angle. An indication of the edges of the normalized processed image histogram for each of the plurality of angles is plotted to form a boundary detection evaluation visualization.
Wantuch, Andrew C.↗
GPU Acceleration of Kernel Density Estimators in Monte Carlo Neutron Transport Simulations
Kernel Density Estimators (KDEs) have recently been explored for use in Monte Carlo radiation transport simulations as an alternative to histogram tallies for capturing spatially-resolved quantities such as neutron flux and reaction rates. Histogram tallies suffer from large uncertainties when detailed spatial resolution of the quantity of interest is required; increasing the resolution of the underlying mesh increases the uncertainty in each histogram bin. KDEs obtain estimates of underlying densities on user-defined points, with the uncertainty at those points being independent of the spatial resolution desired since collisions and particle-track segments are allowed to contribute to the score at multiple tally points. Thus, KDEs show potential for obtaining estimates of a smoother spatially-resolved with reduced variance when compared to a histogram. However, this ability that enables KDEs to obtain lower uncertainties per particle history is more computationally expensive than using a traditional histogram bins on a structured mesh. While KDEs are capable of producing lower tally uncertainties compared to histogram binning for a given number of histories, their increased computational cost may make them less efficient. Even so, it is possible to reduce this additional cost by exporting the KDE tally routines onto Graphics Processing Units (GPUs). GPUs are commonly found on high-performance computing machines as a means of increasing performance without adding additional compute nodes. While it is difficult for existing Monte Carlo radiation transport codes to take advantage of GPUs without rewriting large portions of the code, it is possible to leverage GPUs through heterogeneous computing. This work uses a modified version of OpenMC and exports the KDE tally routines onto a GPU to obtain problem-dependent speedups ranging between 1.6 and 5.0 for the problem studied in this paper. While this methodology is applied to KDEs, the same ideas can be applied to other computationally expensive vectorizable portions of Monte Carlo algorithms. (authors)
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Texture analysis of small renal cell carcinomas at MDCT for predicting relevant histologic and protein biomarkers
Purpose: To assess CT texture features of small renal cell carcinomas (≤ 4cm) for association with key pathologic features including protein biomarkers. Methods: Quantitative CT texture analysis (CTTA) of small renal cancers (≤ 4cm) was performed on non-contrast and portal venous phase abdominal MDCT scans with an ROI drawn at the largest cross-sectional diameter of the tumor using commercially available software. Texture parameters including mean pixel attenuation, the standard deviation (SD) of the pixel distribution histogram, entropy, the mean of positive pixels, the skewness (i.e., asymmetry) of the pixel histogram, kurtosis (i.e., peakness) of the pixel histogram, and the percentage of positive pixels were correlated with pathologic data from surgical resection, including histology and nuclear grade, as well as microarray analysis in a subset (n = 40) including Ki67 index, CRP, and neovascularization (CD105/CD31). Results: Portal venous phase images were available in 249 patients (105 women, 144 men; mean age, 56.7 years) with tumors ≤ 4cm (mean, median, range, ± SD; 2.66, 2.60, 0.3–4.0 ± 0.85 cm). CT texture features of standard deviation, mean of the positive pixels, and entropy of the pixel histogram were significantly associated with histologic cell type (clear vs. non-clear; p < 0.001). Entropy and mean of the positive pixels also showed an association with nuclear grade, although not statistically significant. In the microarray analysis subset, kurtosis of the pixel histogram was associated with CD105/CD31 (p = 0.05). SD also showed some association with CD 105 positivity (p = 0.02) and CAIX expression (p = 0.01). Non-contrast CT images were available in 174 patients (72 women, 102 men; mean age, 57.5 years). Although the association with histology was not as strong as on the portal venous phase, in the subset of patients with microarray data, SD was found to correlate with CRP (p = 0.08), kurtosis with CRP (p = 0.004), CD105/CD31 (p = 0.002), and with Ki 67 index (p < 0.001). Conclusion: CT texture features were significantly associated with important histopathologic features in small renal cancers. These non-invasive measures can be performed retrospectively and may provide useful information when determining follow-up and treatment of small renal cancers.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Cosmic-ray exposure history of ordinary chondrites
The exposure age histograms for H-, L-, and LL-chondrites are discussed. None of these histograms is consistent with a continuous delivery of asteroidal material to the earth, as the observed T(e) histograms clearly disagree with expected exponential distributions for a variety of orbital lifetimes. It is concluded that T(e) histograms are dominated by stochastic events and that the continuous supply of asteroidal material can account only for a minor background of the T(e) histograms. An attempt is made to identify major collisional levels among the major classes of ordinary chondrites in order to estimate the frequency of stochastic events. Orbital maturity in the inner solar system is documented by the p.m./total fall ratio among observed meteorite falls. All chondrite classes exhibit a uniform ratio of 2/3 except type H5 chondrites, which reveal a 0.5 or lower p.m./total fall ratio. This shift in the time of fall statistics suggests a strongly evolved orbit for the H5 parent at the time of collision about 7 Ma ago.
Marti, K.↗
Insights into Long-Term Global Precipitation from IMERG and GPCP
Multiple satellite-based datasets provide estimates of the long-term record of global precipitation. Each necessarily includes both the real atmospheric behavior and a collection of artifacts driven by the input data sources and design choices in the retrievals and dataset construction. For this presentation, the Integrated Multi-satellitE Retrievals for GPM (IMERG) products from the Global Precipitation Measurement (GPM) mission’s U.S. Science Team are designed as a modern High-Resolution Precipitation Product (HRPP), while the Global Precipitation Climatology Project’s (GPCP) products are designed as a modern Climate Data Record (CDR). Although they share some common input data sources, the computational process for each is rather different. Comparing the precipitation estimates from each algorithm gives us insights into likely artifacts and the natural variations that are common to both. The goal of an HRPP is to give the best estimate of precipitation at each time step in the dataset, generally meaning that “all possible available” data are used. In contrast, the CDR is intended to provide a precipitation record that has relatively homogeneous statistics, necessary for climate analysis. Each analysis strives for both goals, of course, but this means that the HRPP uses the disparate collection of satellites whose statistics don’t quite match the ideal record, while the CDR is computed from fewer satellites that provide a relatively homogeneous set of precipitation statistics. This presentation employs the current versions of the IMERG and GPCP products, V07B and V3.2, respectively. A variety of analyses have demonstrated that IMERG has more artifacts, as expected, which tend to result from changes in the source of intercalibration for the various input satellites, namely the Combined Radar-Radiometer Algorithm using TMI and PR during the TRMM era and using GMI and DPR-Ku during the GPM era. As well, a shift occurs when the altitudes of the TRMM and GPM satellites change as a result of orbit boosts. For the most part the mean precipitation shows good continuity across these boundaries, but there are noticeable changes in the respective histograms. The latter has taken on more importance in recent years due to increased scrutiny on extremes which implicitly focus on the upper end of the precipitation histograms. The GPCP product is more homogeneous, with only one major change in calibrator, transitioning from the SSMI series of satellites to the SSMIS series of satellites in 2009. The GPCP analysis does a good job of minimizing artifacts in the means at this boundary, while the histograms show a smaller, but still noticeable shift in the histograms, a result that is similar to data boundaries in IMERG. The GPCP Daily, which is a month-by-month rescaling of the daily accumulated IMERG Final product, shows more consistency than the equivalent daily IMERG, but inherits the histogram shifts from IMERG. Given this overlay of artifacts, there is enough consistency between the products to illustrate some important long-term variations, including interannual variations, not all of which are easily attributable to ENSO events, and trends that are large regionally, but comparatively small when averaged across the globe.
precipitation↗
Validation of the TOPAS Monte Carlo toolkit for HDR brachytherapy simulations
The goal of this work is to validate the user-friendly Geant4-based Monte Carlo toolkit TOol for PArticle Simulation (TOPAS) for brachytherapy applications. Brachytherapy simulations performed with TOPAS were systematically compared with published TG-186 reference data. The photon emission energy spectrum, the air-kerma strength, and the dose-rate constant of the model-based dose calculation algorithm (MBDCA)-WG generic Ir-192 source were extracted. For dose calculations, a track-length estimator was implemented. Additionally, the four Joint AAPM/ESTRO/ABG MBDCA-WG test cases were evaluated through histograms of the local and global dose difference volumes. A prostate, a palliative lung, and a breast case were simulated. For each case, the dose ratio map, the histogram of the global dose difference volume, and cumulative dose-volume histograms were calculated. The air-kerma strength was (9.772 ± 0.001) × 10 -8 U Bq -1 (within 0.3% of the reference value). The dose-rate constant was 1.1107 ± 0.0005 cGy h -1 U -1 (within 0.01% of the reference value). For all cases, at least 96.9% of voxels had a local dose difference within [-1%, 1%] and at least 99.9% of voxels had a global dose difference within [-0.1%, 0.1%]. The implemented track-length estimator scorer was more efficient than the default analog dose scorer by a factor of 237. For all clinical cases, at least 97.5% of voxels had a global dose difference within [-1%, 1%]. Dose-volume histograms were consistent with the reference data. TOPAS was validated for high-dose-rate brachytherapy simulations following the TG-186 recommended approach for MBDCAs. Built on top of Geant4, TOPAS provides broad access to a state-of-the-art Monte Carlo code for brachytherapy simulations.
59 BASIC BIOLOGICAL SCIENCES↗
SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images
Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.
60 APPLIED LIFE SCIENCES↗
The Poisson tensor completion non-parametric differential entropy estimator
We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.
42 ENGINEERING↗