Laser Tracker and Terrestrial Laser Scanner Range Error Evaluation by Stitching.

Laser trackers (LTs) are dimensional measurement instruments commonly employed in the manufacture and assembly of large structures. Terrestrial laser scanners (TLSs) are a related class of dimensional measurement instruments more commonly employed in surveying, reverse engineering, and forensics. Commercially available LTs typically have measurement ranges of up to 80 m. The measurement ranges of TLSs vary from about 50 m to several hundred meters, with some extending as far as several kilometers. It is difficult, if not impossible, to construct long reference lengths to evaluate the ranging performances of these instruments over that distance. In this context, we explore the use of stitching errors (i.e., stacking errors in adjoining or overlapping short lengths) and stitching lengths (i.e., constructing long reference lengths from multiple positions of a reference instrument by registration) to evaluate these instruments. Through experimental data and a discussion on uncertainty, we show that stitching is indeed a viable option to evaluate the ranging performances of LTs and TLSs.

A deep learning-based approach for statistical robustness evaluation in proton therapy treatment planning: a feasibility study.

Objective. Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a consistent statistical interpretation. We propose an artificial intelligence-based approach that overcomes this limitation by predicting a set of percentile dose values at every voxel and allows for the evaluation of planning objectives at specific confidence levels.Approach. We built and trained a deep learning (DL) model to predict the 5th and 95th percentile dose distributions, which corresponds to the lower and upper bounds of a two-tailed 90% confidence interval (CI), respectively. Predictions were made directly from the nominal dose distribution and planning computed tomography scan. The data used to train and test the model consisted of proton plans from 543 prostate cancer patients. The ground truth percentile values were estimated for each patient using 600 dose recalculations representing randomly sampled uncertainty scenarios. For comparison, we also tested whether a common worst-case scenario (WCS) robustness evaluation (voxel-wise minimum and maximum) corresponding to a 90% CI could reproduce the ground truth 5th and 95th percentile doses.Main results. The percentile dose distributions predicted by DL yielded excellent agreements with the ground truth dose distributions, with mean dose errors below 0.15 Gy and average gamma passing rates (GPR) at 1 mm/1% above 93.9, which were substantially better than the WCS dose distributions (mean dose error above 2.2 Gy and GPR at 1 mm/1% below 54). We observed similar outcomes in a dose-volume histogram error analysis, where the DL predictions generally yielded smaller mean errors and standard deviations than the WCS evaluation doses.Significance. The proposed method produces accurate and fast predictions (∼2.5 s for one percentile dose distribution) for a given confidence level. Thus, the method has the potential to improve robustness evaluation.

Weight interpretation of artificial neural network model for analysis of rice (Oryza sativa L.) with near-infrared spectroscopy.

Prediction models for major nutrients of rice were built using near-infrared (NIR) spectral data based on the artificial neural network (ANN). Scientific interpretation of the weight values was proposed and performed to understand the wavenumbers contributing to the prediction of nutrients. NIR spectra were acquired from 110 rice samples. Carbohydrate and moisture contents were predicted with values for the determination coefficient, relative root mean square error, range error ratio, and residual prediction deviation of 0.98, 0.11 %, 44, and 7.3, and 0.97, 0.80 %, 27, and 5.8, respectively. The results agreed well with ones reported in the previous studies and acquired by the conventional partial least squares (PLS)-variable importance in projection method. This study demonstrates that the combination of NIR and ANN is a powerful and accurate tool to monitor nutrients of rice and scientific interpretation of weights can be performed to overcome black box nature of the ANN.

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting.

Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models.Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate.Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ2 mm/2%≥ 99.01% (E[d]),γ2 mm/2%≥ 98.04% (σ(d))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[d])/ 93.70% (σ(d)) (range errors) and 99.86% (E[d])/ 96.64% (σ(d)) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude.Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

Analysis of characteristics of images acquired with a prototype clinical proton radiography system.

PURPOSE: Verification of patient-specific proton stopping powers obtained in the patient's treatment position can be used to reduce the distal and proximal margins needed in particle beam planning. Proton radiography can be used as a pretreatment instrument to verify integrated stopping power consistency with the treatment planning CT. Although a proton radiograph is a pixel by pixel representation of integrated stopping powers, the image may also be of high enough quality and contrast to be used for patient alignment. This investigation quantifies the accuracy and image quality of a prototype proton radiography system on a clinical proton delivery system. METHODS: We have developed a clinical prototype proton radiography system designed for integration into efficient clinical workflows. We tested the images obtained by this system for water-equivalent thickness (WET) accuracy, image noise, and spatial resolution. We evaluated the WET accuracy by comparing the average WET and rms error in several regions of interest (ROI) on a proton radiograph of a custom peg phantom. We measured the spatial resolution on a CATPHAN Line Pair phantom and a custom edge phantom by measuring the 10% value of the modulation transfer function (MTF). In addition, we tested the ability to detect proton range errors due to anatomical changes in a patient with a customized CIRS pediatric head phantom and inserts of varying WET placed in the posterior fossae of the brain. We took proton radiographs of the phantom with each insert in place and created difference maps between the resulting images. Integrated proton range was measured from an ROI in the difference maps. RESULTS: We measured the WET accuracy of the proton radiographic images to be ±0.2 mm (0.33%) from known values. The spatial resolution of the images was 0.6 lp/mm on the line pair phantom and 1.13 lp/mm on the edge phantom. We were able to detect anatomical changes producing changes in WET as low as 0.6 mm. CONCLUSION: The proton radiography system produces images with image quality sufficient for pretreatment range consistency verification.

Practical robustness evaluation in radiotherapy - A photon and proton-proof alternative to PTV-based plan evaluation.

BACKGROUND AND PURPOSE: A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations. MATERIALS AND METHODS: The limitation of the static dose cloud approximation was solved in a multi-scenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans. RESULTS: CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R2 > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R2 > 0.99) and on average needed corrections of -0.9% and +2.3%, respectively. CONCLUSIONS: A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation.

Design, Implementation and Validation of a GNSS Measurement Exclusion and Weighting Function with a Dual Polarized Antenna.

Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures or autonomous vehicles, in which GNSS is an essential tool nowadays. Unfortunately, current GNSS performance is not enough to fulfill the requirements of these professional and critical applications. For this reason, the FANTASTIC project was launched to boost the adoption of these applications. The project was funded by the European GNSS agency (GSA) in order to enhance the robustness and accuracy of GNSS in harsh environments. This paper presents the part related to the development of a weighting and exclusion function with a dual circularly polarized antenna. The idea is to reduce the effects of multipath by weighting and/or excluding those measurements affected by multipath. The observables and other metrics obtained from a dual polarized antenna will be exploited to define an exclusion threshold and to provide the weights. Real-world experiments will show the improvement in the positioning solution, using all available constellations, obtained with the developed technique.

Real-Time Monitoring for BDS Signal-In-Space Anomalies Using Ground Observation Data.

Signal-in-space (SIS) User Range Error (URE) is one of the major error sources for BeiDou Navigation Satellite System (BDS) applications and can reach tens of meters or even more. Therefore, real-time monitoring of SIS anomalies has a great realistic significance to guarantee the safety of users. According to an analysis of the BDS navigation messages, it showed that the User Range Accuracy (URA) index could not reflect the change of URE when it was abnormal. The conventional models using the relationship between URA and URE to monitor SIS anomalies are not suitable to the present BDS. Therefore, we use a prior information of SIS URE derived from ground observational data instead of URA to monitor BDS SIS anomalies. In order to realize the corresponding functions, we analysed the distribution of SIS UREs and obtained their prior models. Then, the monitoring threshold is determined using the prior models and a confidence interval instead of URA. The scheme was tested by applying to BDS SIS anomalies monitoring based on 13 ground tracking stations. The performance of this method was assessed by comparison with the satellite-health indicators from broadcast ephemeris. The results confirm that the method developed in this paper can rightly and timely detect abnormal SIS.

Reading sentences of uniform word length - II: Very rapid adaptation of the preferred saccade length.

In the current study we investigated whether readers adjust their preferred saccade length (PSL) during reading on a trial-by-trial basis. The PSL refers to the distance between a saccade launch site and saccade target (i.e., the word center during reading) when participants neither undershoot nor overshoot this target (McConkie, Kerr, Reddix, & Zola in Vision Research, 28, 1107-1118, 1988). The tendency for saccades longer or shorter than the PSL to under or overshoot their target is referred to as the range error. Recent research by Cutter, Drieghe, and Liversedge (Journal of Experimental Psychology: Human Perception and Performance, 2017) has shown that the PSL changes to be shorter when readers are presented with 30 consecutive sentences exclusively made of three-letter words, and longer when presented with 30 consecutive sentences exclusively made of five-letter words. We replicated and extended this work by this time presenting participants with these uniform sentences in an unblocked design. We found that adaptation still occurred across different sentence types despite participants only having one trial to adapt. Our analyses suggested that this effect was driven by the length of the words readers were making saccades away from, rather than the length of the words in the rest of the sentence. We propose an account of the range error in which readers use parafoveal word length information to estimate the length of a saccade between the center of two parafoveal words (termed the Centre-Based Saccade Length) prior to landing on the first of these words.

Concept to Commercialization of an Artifact for Evaluating Three-Dimensional Imaging Systems per ASTM E3125-17.

The relative-range error test is one of several tests described in the ASTM E3125-2017 standard for performance evaluation of spherical coordinate three-dimensional (3D) imaging systems such as terrestrial laser scanners (TLS). We designed a new artifact, called the plate-sphere target, that allows the realization of the relative-range error tests quickly and efficiently without the need for alignment at each position of the test.Use of a simple planar/plate target requires careful alignment of the target at each position of the relative-range error test, which is labor-intensive and time-consuming. This new artifact significantly reduces the time required to perform the test, from a matter of about 2 h to less than 30 min while resulting in similar test uncertainty values.The plate-sphere target was conceived and initially developed at the National Institute of Standards and Technology (NIST), improved based on feedback from collaborators at the National Research Council (NRC) of Canada and TLS manufacturers, and commercialized by Bal-tec Inc.This new artifact will save users and manufacturers of TLSs considerable time and money.

Relative range error evaluation of terrestrial laser scanners using a plate, a sphere, and a novel dual-sphere-plate target.

Terrestrial laser scanners (TLS) are a class of 3D imaging systems that produce a 3D point cloud by measuring the range and two angles to a point. The fundamental measurement of a TLS is range. Relative range error is one component of the overall range error of TLS and its estimation is therefore an important aspect in establishing metrological traceability of measurements performed using these systems. Target geometry is an important aspect to consider when realizing the relative range tests. The recently published ASTM E2938-15 mandates the use of a plate target for the relative range tests. While a plate target may reasonably be expected to produce distortion free data even at far distances, the target itself needs careful alignment at each of the relative range test positions. In this paper, we discuss relative range experiments performed using a plate target and then address the advantages and limitations of using a sphere target. We then present a novel dual-sphere-plate target that draws from the advantages of the sphere and the plate without the associated limitations. The spheres in the dual-sphere-plate target are used simply as fiducials to identify a point on the surface of the plate that is common to both the scanner and the reference instrument, thus overcoming the need to carefully align the target.