Intensity Errors Research Articles

Tropical Cyclone Intensity Errors Associated with Lack of Two-Way Ocean Coupling in High-Resolution Global Simulations

AbstractTropical cyclones (TCs), particularly those that are intense and/or slow moving, induce sea surface temperature (SST) reductions along their tracks (commonly referred to as cold wakes) that provide a negative feedback on storm energetics by weakening surface enthalpy fluxes. While computing gains have allowed for simulated TC intensity to increase in global climate models as a result of increased horizontal resolution, many configurations utilize prescribed, noninteractive SSTs as a surface boundary condition to minimize computational cost and produce more accurate TC climatologies. Here, an idealized slab ocean is coupled to a 0.25° variable-resolution version of the Community Atmosphere Model (CAM) to improve closure of the surface energy balance and reproduce observed Northern Hemisphere cold wakes. This technique produces cold wakes that are realistic in structure and evolution and with magnitudes similar to published observations, without impacting large-scale SST climatology. Multimember ensembles show that the overall number of TCs generated by the model is reduced by 5%–9% when allowing for two-way air–sea interactions. TC intensity is greatly impacted; the strongest 1% of all TCs are 20–30 hPa (4–8 m s−1) weaker, and the number of simulated Saffir–Simpson category 4 and 5 TCs is reduced by 65% in slab ocean configurations. Reductions in intensity are in line with published thermodynamic theory. Additional offline experiments and sensitivity simulations demonstrate this response is both significant and robust. These results imply caution should be exercised when assessing high-resolution prescribed SST climate simulations capable of resolving intense TCs, particularly if discrete analysis of extreme events is desired.

A comparison of ground-based LiDAR and met mast wind measurements for wind resource assessment over various terrain conditions

In order to assess reliability of measurements from LiDAR (Light Detection and Ranging), a measurement campaign was led using ground-based LiDAR of WINDCUBE V2 and meteorological masts at three measurement sites: Sumang, Gangjeong, and Susan, on Jeju Island, Korea. Each site had a different topographical complexity, which was evaluated by using a Ruggedness Index (RIX). Wind data was collected for 11−14 days from four heights on each site's met mast. Data filtering was done to ensure data comparability between LiDAR and wind sensors. Analyses of LiDAR error, standard deviation, turbulence intensity and LiDAR error rate were conducted on data coming from each site. Also, the CFD analysis was performed at Sumang with the highest RIX. As a result, the concurrent wind measurement slopes were all close to one based on linear regression analysis. The coefficient of determination was almost all more than 0.9 for all heights at each site. LiDAR error rates for the measurement sites ranged approximately between 2% and 6%. The result of the CFD analysis showed that the depression was formed between two parasitic cones, between which the measurement point of Sumang was located, which led to greater positive LiDAR error.

Hurricane Intensity Predictability

Abstract Weather has long been projected to possess limited predictability due to the inherent chaotic nature of the atmosphere; small changes in initial conditions could lead to an entirely different state of the atmosphere after some period of time. Given such a limited range of predictability of atmospheric flows, a natural question is, how far in advance can we predict a hurricane’s intensity? In this study, it is shown first that the predictability of a hurricane’s intensity at the 4–5-day lead times is generally determined more by the large-scale environment than by a hurricane’s initial conditions. This result suggests that future improvement in hurricane longer-range intensity forecasts by numerical models will be most realized as a result of improvement in the large-scale environment rather than in the storm’s initial state. At the mature stage of a hurricane, direct estimation of the leading Lyapunov exponent using an axisymmetric model reveals, nevertheless, the existence of a chaotic attractor in the phase space of the hurricane scales. This finding of a chaotic maximum potential intensity (MPI) attractor provides direct information about the saturation of a hurricane’s intensity errors around 8 m s−1, which prevents the absolute intensity errors at the mature stage from being reduced below this threshold. The implication of such intensity error saturation to the limited range of hurricane intensity forecasts will be also discussed.

Anaglyph Caustics with Motion Parallax

AbstractIn this paper we present a method to model and simulate a lens such that its caustic reveals a stereoscopic 3D image when viewed through anaglyph glasses. By interpreting lens dispersion as stereoscopic disparity, our method optimizes the shape and arrangement of prisms constituting the lens, such that the resulting anaglyph caustic corresponds to a given input image defined by intensities and disparities. In addition, a slight change of the lens' distance to the screen causes a 3D parallax effect that can also be perceived without glasses. Our proposed relaxation method carefully balances the resulting pixel intensity and disparity error, while taking the subsequent physical fabrication process into account. We demonstrate our method on a representative set of input images and evaluate the anaglyph caustics using multi‐spectral photon tracing. We further show the fabrication of prototype lenses with a laser cutter as a proof of concept.

In-focus quantitative intensity and phase imaging with the numerical focusing transport of intensity equation method

Microscopy combined with the transport of intensity equation is capable of retrieving both intensity and phase distributions of samples from both in-focus and defocus intensities. However, during measurements, the focal plane is often decided artificially and the improper choice may induce errors in quantitative intensity and phase retrieval. In order to obtain accurate in-focus information, quantitative intensity and phase imaging with the numerical focusing transport of intensity equation method combined with cellular duty ratio criterion and numerical wavefront propagation is introduced in this paper. Both numerical simulations and experimental measurements are provided proving this designed method can increase both retrieved in-focus intensity and phase accuracy and reduce dependence of focal plane determination in transport of intensity equation measurements. It is believed that the proposed method can be potentially applied in various fields as in-focus compensation for quantitative phase imaging and automatic focal plane determination, etc.

On the Predictability and Error Sources of Tropical Cyclone Intensity Forecasts

Abstract The skill of tropical cyclone intensity forecasts has improved slowly since such forecasts became routine, even though track forecast skill has increased markedly over the same period. In deciding whether or how best to improve intensity forecasts, it is useful to estimate fundamental predictability limits as well as sources of intensity error. Toward that end, the authors estimate rates of error growth in a “perfect model” framework in which the same model is used to explore the sensitivities of tropical cyclone intensity to perturbations in the initial storm intensity and large-scale environment. These are compared to estimates made in previous studies and to intensity error growth in real-time forecasts made using the same model, in which model error also plays an important role. The authors find that error growth over approximately the first few days in the perfect model framework is dominated by errors in initial intensity, after which errors in forecasting the track and large-scale kinematic environment become more pronounced. Errors owing solely to misgauging initial intensity are particularly large for storms about to undergo rapid intensification and are systematically larger when initial intensity is underestimated compared to overestimating initial intensity by the same amount. There remains an appreciable gap between actual and realistically achievable forecast skill, which this study suggests can best be closed by improved models, better observations, and superior data assimilation techniques.

Impact of air‐sea coupling on the simulation of tropical cyclones in the North Indian Ocean using a simple 3‐D ocean model coupled to ARW

AbstractIn this work, the impact of air‐sea coupling on tropical cyclone (TC) predictions is studied using a three‐dimensional Price‐Weller‐Pinkel (3DPWP) ocean model coupled to the Advanced Research Weather Research and Forecasting in six tropical storms in the North Indian Ocean, representing different intensities, seasonality, and varied oceanic conditions. A set of numerical experiments are conducted for each cyclone using sea surface temperature (SST) boundary conditions derived from Global Forecast System (GFS) SST, NOAA/National Centers for Environmental Prediction SST, and ocean coupling (3DPWP). Significant differences and improvements are found in the predicted intensity and track in the simulations, in which the cyclones' impact on SST is included. It has been found that while the uncoupled model using GFS SST considerably overestimated the intensity as well as produced large track errors, the ocean coupling substantially improved the track and intensity predictions. The improvements with 3DPWP are because of simulating the ocean‐atmosphere feedback in terms of deepening of ocean mixed layer, reduction in enthalpy fluxes, and storm‐induced SST cooling as seen in observations. The coupled model could simulate the cold wake in SST, asymmetries in the surface winds, enthalpy fluxes, size, and structure of the storm in better agreement with observations than the uncoupled model. The coupled model reduced the track errors by roughly 0.3–39% and intensity errors by 29–47% at 24–96 h predictions by controlling the northward deviation of storms tracks by SST cooling and associated changes in the dynamics. The vorticity changes associated with horizontal advection and stretching terms affect the tracks of the storms in the three simulations.

Accuracy of Estimating Step Counts and Intensity Using Accelerometers in Older People With or Without Assistive Devices.

The purpose of this study was to examine the accuracy of uni- and triaxial accelerometers in monitoring step counts and gait intensity in older people who did or did not use an assistive device. Forty-nine healthy and frail older adults wore uniaxial (Lifecorder, Suzuken Co. Ltd.) and triaxial accelerometers (Activity Monitor, Matsushita Electronic Works, Ltd., and Active Style Pro, Omron Healthcare Co., Ltd.) during three trials at different gait speeds. All accelerometers gave relatively accurate step counts for healthy older participants compared with direct observation; however, the error was greater for frail older people with assistive devices. Gait intensity detection error was unaffected by gait speed. Among frail older people with assistive devices, the gait intensity error was smaller than for step count error. To accurately assess the steps walked or the gait intensity among frail older people using assistive devices, more study is needed on these groups of participants.

Interferometric measurement of surface shape by wavelength tuning suppressing random intensity error.

In this research, the susceptibility of the phase-shifting algorithms to the random intensity error is formulated and estimated. The susceptibility of the random intensity error of conventional windowed phase-shifting algorithms is discussed, and the 7N-6 phase-shifting algorithm is developed to minimize the random intensity error using the characteristic polynomial theory. Finally, the surface shape of the transparent wedge plate is measured using a wavelength-tuning Fizeau interferometer and the 7N-6 algorithm. The experimental results indicate that the surface shape measurement accuracy for the transparent plate is 2.5 nm.

Quantitative and In-Depth Survey of the Isotopic Abundance Distribution Errors in Shotgun Proteomics.

Accuracy is an important metric when mass spectrometry (MS) is used in large-scale quantitative proteomics research. For MS-based quantification by extracting ion chromatogram (XIC), both the mass and intensity dimensions must be accurate. Although much research has focused on mass accuracy in recent years, less attention has been paid to intensity errors. Here, we investigated signal intensity measurement errors systematically and quantitatively using the natural properties of isotopic distributions. First, we defined a normalized isotopic abundance error model and presented its merits and demerits. Second, a comprehensive survey of the isotopic abundance errors using data sets with increasing sample complexities and concentrations was performed. We examined parameters such as error distribution, relationships between signal intensities within one isotopic cluster, and correlations between different peak errors in isotopic profiles. Our data demonstrated that the high resolution MS platforms might also generate large isotopic intensity measurement errors (approximately 20%). Meanwhile, this error can be reduced to less than 5% using a novel correction algorithm, which is based on the theoretical isotopic abundance distribution. Finally, a nonlinear relationship was observed as the abundance error decreased in isotopic profiles with higher intensity. Our findings are expected to provide insight into isotopic abundance recalibration in quantitative proteomics.

TU‐AB‐202‐04: Development of a DeformableImage Registration (DIR) Error Correction Method Employing Kolmogorov‐Zurbenko(KZ) Filter

Purpose:This study aims to develop a DIR error correction method capable of utilizing sparse ground‐truth motion information and recovering missing data with the Kolmogorov‐Zurbenko (KZ) filter.Methods:The error correction method employs a two‐step approach. First, sparse ground‐truth displacement vectors are integrated into a pre‐correction deformable vector field (DVF) to estimate a post‐correction DVF with coarse resolution. Second, the coarse post‐correction DVF is boosted to a full‐resolution DVF through convolution with the KZ filter. To validate the use of the KZ filter for missing data recovery, recovery errors were determined by comparing a DVF recovered from down‐sampling with the original full‐resolution DVF. The entire error correction method was tested on an in‐house developed digital lung motion phantom consisting of a primary volume, a DVF, and a secondary volume synthesized by applying the DVF on the primary volume. Five pre‐correction DVFs were obtained by performing DIR between the two volumes using Velocity, MIM, ILK and OHS algorithms in DIRART toolbox, and Elastix, and then corrected. Primary volumes were synthesized with pre‐ and post‐correction DVFs, respectively. The error correction method was evaluated with pre‐ and post‐correction registration errors, and intensity errors in synthesized primary volumes.Results:Our test results for sparsely down‐sampled (<0.4%) DVFs showed that the KZ filter outperformed the cubic polynomial interpolation method for whole lung DVF map recovery in terms of median error (0.60mm vs 0.73mm) and mean error (1.18mm vs 1.29mm). Pre‐ and post‐correction 3D registration errors per voxel for Velocity, MIM, ILK, OHS, and Elastix are reduced by 2.39 mm on average. Pre‐ and post‐correction intensity errors are reduced by 0.37 in unit of image intensity on average.Conclusion:We have implemented a two‐step method capable of utilizing sparse ground‐truth displacement vectors for DIR error reduction, allowing DIR accuracy improvement utilizing clinically available motion data.This study is supported by NIH grant 1R21CA165384.

WE‐AB‐202‐07: Ventilation CT: Voxel‐Level Comparison with Hyperpolarized Helium‐3 & Xenon‐129 MRI

Purpose:To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath‐hold CT with hyperpolarized Helium‐3 & Xenon‐129 MRI in a cohort of lung cancer patients.Methods:5 patients underwent expiration & inspiration breath‐hold CT. Xenon‐129 & 1H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium‐3 & 1H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel‐wise differences in Hounsfield units. Inspiration CT and the Xenon‐129's corresponding anatomical 1H MRI were registered to Helium‐3 MRI via the same‐breath anatomical 1H MRI. This enabled direct comparison of CT ventilation with Helium‐3 MRI & Xenon‐129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in‐plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same‐breath 1H MRI lung mask. Spearman coefficients were used to assess voxel‐level correlation.Results:The median Spearman's coefficients of ventilation CT with Helium‐3 & Xenon‐129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively.Conclusion:This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium‐3 & Xenon‐129 MRI) in similar breath‐holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non‐ventilatory effects and registration errors at the voxel‐level. Thus, it may be more beneficial to quantify ventilation at a more regional level.

Restoration of Thickness, Density, and Volume for Highly Blurred Thin Cortical Bones in Clinical CT Images.

In clinical CT images containing thin osseous structures, accurate definition of the geometry and density is limited by the scanner's resolution and radiation dose. This study presents and validates a practical methodology for restoring information about thin bone structure by volumetric deblurring of images. The methodology involves 2 steps: a phantom-free, post-reconstruction estimation of the 3D point spread function (PSF) from CT data sets, followed by iterative deconvolution using the PSF estimate. Performance of 5 iterative deconvolution algorithms, blind, Richardson-Lucy (standard, plus Total Variation versions), modified residual norm steepest descent (MRNSD), and Conjugate Gradient Least-Squares were evaluated using CT scans of synthetic cortical bone phantoms. The MRNSD algorithm resulted in the highest relative deblurring performance as assessed by a cortical bone thickness error (0.18mm) and intensity error (150HU), and was subsequently applied on a CT image of a cadaveric skull. Performance was compared against micro-CT images of the excised thin cortical bone samples from the skull (average thickness 1.08±0.77mm). Error in quantitative measurements made from the deblurred images was reduced 82% (p<0.01) for cortical thickness and 55% (p<0.01) for bone mineral mass. These results demonstrate a significant restoration of geometrical and radiological density information derived for thin osseous features.

Depth estimation and camera calibration of a focused plenoptic camera for visual odometry

This paper presents new and improved methods of depth estimation and camera calibration for visual odometry with a focused plenoptic camera.For depth estimation we adapt an algorithm previously used in structure-from-motion approaches to work with images of a focused plenoptic camera. In the raw image of a plenoptic camera, scene patches are recorded in several micro-images under slightly different angles. This leads to a multi-view stereo-problem. To reduce the complexity, we divide this into multiple binocular stereo problems. For each pixel with sufficient gradient we estimate a virtual (uncalibrated) depth based on local intensity error minimization. The estimated depth is characterized by the variance of the estimate and is subsequently updated with the estimates from other micro-images. Updating is performed in a Kalman-like fashion. The result of depth estimation in a single image of the plenoptic camera is a probabilistic depth map, where each depth pixel consists of an estimated virtual depth and a corresponding variance.Since the resulting image of the plenoptic camera contains two plains: the optical image and the depth map, camera calibration is divided into two separate sub-problems. The optical path is calibrated based on a traditional calibration method. For calibrating the depth map we introduce two novel model based methods, which define the relation of the virtual depth, which has been estimated based on the light-field image, and the metric object distance. These two methods are compared to a well known curve fitting approach. Both model based methods show significant advantages compared to the curve fitting method.For visual odometry we fuse the probabilistic depth map gained from one shot of the plenoptic camera with the depth data gained by finding stereo correspondences between subsequent synthesized intensity images of the plenoptic camera. These images can be synthesized totally focused and thus finding stereo correspondences is enhanced. In contrast to monocular visual odometry approaches, due to the calibration of the individual depth maps, the scale of the scene can be observed. Furthermore, due to the light-field information better tracking capabilities compared to the monocular case can be expected.As result, the depth information gained by the plenoptic camera based visual odometry algorithm proposed in this paper has superior accuracy and reliability compared to the depth estimated from a single light-field image.

Two-way information sharing under supply chain competition

We study manufacturer-retailer bilateral information sharing in two competing supply chains (SCs), in which both the manufacturer and the retailer have partial information on demand. Based on Bertrand competition model and Winkler's consensus model, we develop a finite Bayesian Stackelberg game to analyze the two-way information sharing problem under horizontal supply chain (SC) competition. In line with the literature, we find that sharing demand forecast voluntarily in a SC benefits the manufacturer but hurts the retailer. However, we find whether SCs benefit from information sharing depends on competition intensity and forecast error. As competition is intensive, the expected values of information sharing (EVISs) for the entire SCs are high. Moreover, information sharing in one supply chain can improve the rival supply chain's EVIS under some conditions. Numerical experiments are conducted to get some managerial insights.

Simplified and optimized multispectral imaging for 5-ALA-based fluorescence diagnosis of malignant lesions.

5-aminolevulinic acid (5-ALA)-based fluorescence diagnosis is now clinically applied for accurate and ultrarapid diagnosis of malignant lesions such as lymph node metastasis during surgery. 5-ALA-based diagnosis evaluates fluorescence intensity of a fluorescent metabolite of 5-ALA, protoporphyrin IX (PPIX); however, the fluorescence of PPIX is often affected by autofluorescence of tissue chromophores, such as collagen and flavins. In this study, we demonstrated PPIX fluorescence estimation with autofluorescence elimination for 5-ALA-based fluorescence diagnosis of malignant lesions by simplified and optimized multispectral imaging. We computationally optimized observation wavelength regions for the estimation of PPIX fluorescence in terms of minimizing prediction error of PPIX fluorescence intensity in the presence of typical chromophores, collagen and flavins. By using the fluorescence intensities of the optimized wavelength regions, we verified quantitative detection of PPIX fluorescence by using chemical mixtures of PPIX, flavins, and collagen. Furthermore, we demonstrated detection capability by using metastatic and non-metastatic lymph nodes of colorectal cancer patients. These results suggest the potential and usefulness of the background-free estimation method of PPIX fluorescence for 5-ALA-based fluorescence diagnosis of malignant lesions, and we expect this method to be beneficial for intraoperative and rapid cancer diagnosis.

Multi-Repeated Projection Lithography for High-Precision Linear Scale Based on Average Homogenization Effect.

A multi-repeated photolithography method for manufacturing an incremental linear scale using projection lithography is presented. The method is based on the average homogenization effect that periodically superposes the light intensity of different locations of pitches in the mask to make a consistent energy distribution at a specific wavelength, from which the accuracy of a linear scale can be improved precisely using the average pitch with different step distances. The method’s theoretical error is within 0.01 µm for a periodic mask with a 2-µm sine-wave error. The intensity error models in the focal plane include the rectangular grating error on the mask, static positioning error, and lithography lens focal plane alignment error, which affect pitch uniformity less than in the common linear scale projection lithography splicing process. It was analyzed and confirmed that increasing the repeat exposure number of a single stripe could improve accuracy, as could adjusting the exposure spacing to achieve a set proportion of black and white stripes. According to the experimental results, the effectiveness of the multi-repeated photolithography method is confirmed to easily realize a pitch accuracy of 43 nm in any 10 locations of 1 m, and the whole length accuracy of the linear scale is less than 1 µm/m.

북서태평양 태풍 강도 가이던스 모델 성능평가

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.

Radiometric Calibration of a Dual-Wavelength, Full-Waveform Terrestrial Lidar.

Radiometric calibration of the Dual-Wavelength Echidna® Lidar (DWEL), a full-waveform terrestrial laser scanner with two simultaneously-pulsing infrared lasers at 1064 nm and 1548 nm, provides accurate dual-wavelength apparent reflectance (ρapp), a physically-defined value that is related to the radiative and structural characteristics of scanned targets and independent of range and instrument optics and electronics. The errors of ρapp are 8.1% for 1064 nm and 6.4% for 1548 nm. A sensitivity analysis shows that ρapp error is dominated by range errors at near ranges, but by lidar intensity errors at far ranges. Our semi-empirical model for radiometric calibration combines a generalized logistic function to explicitly model telescopic effects due to defocusing of return signals at near range with a negative exponential function to model the fall-off of return intensity with range. Accurate values of ρapp from the radiometric calibration improve the quantification of vegetation structure, facilitate the comparison and coupling of lidar datasets from different instruments, campaigns or wavelengths and advance the utilization of bi- and multi-spectral information added to 3D scans by novel spectral lidars.

Margin evaluation of translational and rotational set-up errors in intensity modulated radiotherapy for cervical cancer.

A clinical target volume (CTV) to planning target volume (PTV) margin recipes was routinely used to ensure dose was actually delivered to target for all (most) patients. Currently used margin recipes were associated with only translational set-up errors in radiotherapy. However, when set-up errors extended to six-degree (6D) scope (three translational and three rotational set-up errors), margin recipe should be re-evaluated. The purpose of this study was to investigate dosimetric changes of targets (both CTV and PTV) coverage when 6D set-up errors were introduced and testify the practicability of currently used margin recipe in radiotherapy. A total number of 105 cone beam computer tomography scans for ten patients with cervical cancer were derived prior to treatment delivery and 6D set-up errors were acquired with image registration tools. Target coverage was evaluated retrospectively for 6D set-up errors introduced plan with 6 mm CTV to PTV margin. Target coverage of PTV showed significant decreases (3.3 %) in set-up errors introduced plans compared with original plans. But CTV coverage was not susceptible to these set-up errors. A tendency of coverage decrease for PTV along with distance away from treatment was testified, from −0.2 to −6.2 %. However, CTV seems changed less, from −0.2 to −0.8 %. The result indicate that a CTV to PTV margin of 6 mm was sufficient to take into account 6D set-up errors for most patients with cervical cancer. Future research suggests a smaller margin to further improve both tumor coverage and organs at risk sparing.