Greater Error Research Articles

The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI.

Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. The under sampled data were reconstructed at 5 s temporal resolution using the data-driven low-rank temporal model for MOCCO, compressed sensing with temporal total variation (CS-TV) and more conventional low-rank reconstruction (PCB). Our results demonstrated that MOCCO was able to recover curves with Ktrans values ranging from 0.01 to 0.8 min−1 and fixed Ve = 0.3, where the fitted results are within a 10% bias error range. MOCCO reconstruction showed less impact on the selection of different temporal models than conventional low-rank reconstruction and the greater error was observed with PCB. CS-TV showed overall underestimation in both Ktrans and Ve. For the Monte-Carlo simulations, MOCCO was found to provide the most accurate reconstruction results for curves with intermediate lesion kinetics in the presence of noise. Initial in vivo experiences are reported in one patient volunteer. Overall, MOCCO was able to provide reconstructed time-series data that resulted in a more accurate measurement of PK parameters than PCB and CS-TV.

Study of Surface Temperature Distribution for High-Temperature U75V Rail Steel Plates in Rolling Process by Colorimetry Thermometry

Surface temperature is a critical operating parameter that influences the phase transition time and rolling quality of U75V rail steel plates in the rolling process. There is still no extensive online detection system for the surface temperature of rail steel plates due to the hazardous environment, incorrect surface emissivity, and complex backgrounds. In this paper, online surface temperature detection equipment based on multi-spectral photography was built for high-temperature rail steel plates in the rolling processes. Then, the emissivity model for a high-temperature environment, colorimetric thermometry, and noise filtering methods were investigated to improve the accuracy of the temperature detection results of rail steel plates. Finally, the surface temperature of the U75V rail steel plate during three rolling passes could be calculated online point by point, and the greatest error was approximately 0.82% due to the blackbody calibration experiments. The results not only have a positive effect on understanding the temperature declination process of low-alloy rail steel plates during the rolling process, but could also benefit the control of the cooling rate and optimize the rolling model during rolling passes.

Monocular 3D object detection with Pseudo-LiDAR confidence sampling and hierarchical geometric feature extraction in 6G network

The high bandwidth and low latency of 6G network technology enable the successful application of monocular 3D object detection on vehicle platforms. Monocular 3D-object-detection-based Pseudo-LiDAR is a low-cost, low-power solution compared to LiDAR solutions in the field of autonomous driving. However, this technique has some problems, i.e., (1) the poor quality of generated Pseudo-LiDAR point clouds resulting from the nonlinear error distribution of monocular depth estimation and (2) the weak representation capability of point cloud features due to the neglected global geometric structure features of point clouds existing in LiDAR-based 3D detection networks. Therefore, we proposed a Pseudo-LiDAR confidence sampling strategy and a hierarchical geometric feature extraction module for monocular 3D object detection. We first designed a point cloud confidence sampling strategy based on a 3D Gaussian distribution to assign small confidence to the points with great error in depth estimation and filter them out according to the confidence. Then, we present a hierarchical geometric feature extraction module by aggregating the local neighborhood features and a dual transformer to capture the global geometric features in the point cloud. Finally, our detection framework is based on Point-Voxel-RCNN (PV-RCNN) with high-quality Pseudo-LiDAR and enriched geometric features as input. From the experimental results, our method achieves satisfactory results in monocular 3D object detection.

Errors of Measurement for Blood Parameters and Physiological and Performance Measures After the Decay of Short-Term Heat Acclimation

Introduction: It is important to determine the accuracy of measurements relative to potential treatment effects, with time intervals between tests. Purpose: The aim of this study was to assess the error of measurement for blood parameters, physiological, and performance measures after the decay of short-term heat acclimation. Methods: Ten trained males (Mean±SD: age 28±7 y; body mass 74.6±4.4 kg; 4.26±0.37 L.min-1; peak power output (PPO) 329±42 W) completed an exercising heat stress test (HST) at baseline, 2nd day after acclimation and then during decay at 1, 2, 3 and 5-6 wks. CoV (95% CI), SE (95% CI) and Pearsons (r) were used for analysis of blood volume (blood, plasma, red cell volume, mean hemoglogin mass); plasma (aldosterone, arginine vasopressin [AVP], total protein, albumin, sodium); physiological (rectal temperature, cardiac frequency) and performance (exercise performance capacity, PPO). Results: The CoV (95% CI), SE (95% CI) and r with a 1-wk interval for blood volume was 2.3% (1.6 to 4.3; 1.9 [1.3 to 3.4 mL.Kg-1]; r=0.93; n=10). After 2-wk and 5-6 wks this had increased to 4.9% (3.4 to 9.3; 3.8 [2.6 to 7.0 mL.Kg-1]; r=0.76; n=9) and 5.5% (3.6 to 12.8; 4.5 [2.9 to 10.0 mL.Kg-1]; r=0.65; n=7) respectively. Conclusions: Blood volume and physiological measures demonstrated the least error one week apart but increased thereafter. Plasma concentrations and performance markers had the greatest error with repeat measures after one week. Therefore, for greater reliability and low measurement error measures should be taken no more than one week a part in repeated experimentation.

Drag Coefficient Constraints for Space Weather Observations in the Upper Thermosphere

AbstractThe space weather research community relies heavily on thermospheric density data to understand long‐term thermospheric variability, construct assimilative, empirical, and semiempirical global atmospheric models and validate model performance. One of the challenges in resolving accurate thermospheric density data sets from satellite orbital drag measurements is modeling appropriate physical aerodynamic drag force coefficients. The drag coefficient may change throughout the thermosphere due to model dependencies on composition and altitude. As such, existing drag coefficient model errors and corresponding errors in orbit‐derived density data sets and models may be altitude and solar cycle dependent with greater errors at higher altitudes around 500 km near the oxygen‐to‐helium transition region. In this paper, inter‐satellite observed‐to‐modeled density comparisons at ∼500 km are evaluated to constrain drag coefficient modeling assumptions. Observed densities are derived from accelerometer data for the Gravity Recovery and Climate Experiment (GRACE) satellites and Two‐Line Element data for a set of compact satellites, while the NRLMSISE‐00 atmospheric model is used to obtain modeled densities and composition information. Density consistency results indicate that drag coefficient models with incomplete energy and momentum accommodation produce the most consistent densities, while the standard diffuse modeling approach may not be appropriate at these altitudes. Models with momentum accommodation between 0.5 and 0.9 and energy accommodation between 0.83 and 0.96 may be most appropriate at upper thermospheric altitudes. Modeling drag coefficients with diffuse gas‐surface interactions for the GRACE satellites could lead to errors in derived density of ∼25% and in‐track satellite orbit prediction uncertainty during solar maximum conditions on the order of kilometers.

A prediction method of vapor pressures for pure substances

From the viewpoint of engineering, a new prediction method of vapor pressures was proposed by directly determining the coefficients of the vapor pressure equation from a boiling point, or a single point vapor pressure data (Ohe, 2019). The proposed method was applied for various kinds of organic substances with satisfactory accuracy. It has the potential to be applied for inorganic substances, since it has no limitation for predicting vapor pressures. In this paper, the method is applied to thirty-seven inorganic substances: rare-earth elements, general inorganic substances, isotopes, and the whole average error is 5.04% with satisfactory accuracy. When predicting, the temperature range of the predicted vapor pressure and the reference vapor pressure must be in agreement with each other. The reason is that even for the same substance, the coefficients of the vapor pressure equation differ when the temperature range is different, resulting in greater error. The Clausius-Clapeyron and the Antoine equations were selected as the vapor pressure ones. Various vapor pressure equations have been proposed, but since the method uses a slope in the straight line of the logarithmic value of the vapor pressure against the reciprocal of the absolute temperature, other equations cannot be used. Furthermore, the Wagner equation requires a critical constant and cannot be used to estimate substances that have only boiling point data. However, if the temperature range is not wide, the Antoine equation can be calculated with the same accuracy as the Wagner equation.

Localized Method of Fundamental Solutions for Two-Dimensional Inhomogeneous Inverse Cauchy Problems

Due to the fundamental solutions are employed as basis functions, the localized method of fundamental solution can obtain more accurate numerical results than other localized methods in the homogeneous problems. Since the inverse Cauchy problem is ill posed, a small disturbance will lead to great errors in the numerical simulations. More accurate numerical methods are needed in the inverse Cauchy problem. In this work, the LMFS is firstly proposed to analyze the inhomogeneous inverse Cauchy problem. The recursive composite multiple reciprocity method (RC-MRM) is adopted to change original inhomogeneous problem into a higher-order homogeneous problem. Then, the high-order homogeneous problem can be solved directly by the LMFS. Several numerical experiments are carried out to demonstrate the efficiency of the LMFS for the inhomogeneous inverse Cauchy problems.

In vitro comparative analysis of scanning accuracy of intraoral and laboratory scanners in measuring the distance between multiple implants

BackgroundThe purpose of this study was to evaluate the accuracy of intraoral scanners by comparing the trueness and precision of several types of scanners in measuring the distance between the ball abutments on pairs of multiple implants.MethodsSeven implants were placed on a fully edentulous upper jaw model. After ball abutments were attached to the implants on the master model, the three-dimensional (3D) shape of the model was evaluated using a computer numerical control 3D coordinate-measuring machine. Subsequently, the 3D shape-related data of the model were obtained using two types of intraoral scanners (3M True Definition Scanner [TDS] and 3Shape Trios3 [TR3]) and two types of laboratory scanners (KaVo ARCTICA Auto Scan [KA] and Identica Hybrid [IH]). Using the obtained 3D shape-related data, the trueness and precision in measuring the distance between the balls within seven pairs of ball abutments were compared among the scanners using 3D analysis software.ResultsIntraoral scanners produced significantly greater errors in trueness and precision than laboratory scanners in measuring the distances between the ball abutments in all the dental regions. Between the intraoral scanners, powder-requiring TDS produced significantly lower errors at inflection points than powder-free TR3.ConclusionsThese results indicate that an optical impression technique using an intraoral scanner is suitable for dental implant treatment in patients with a few missing teeth.

DERVISH LODGES AND CONVENTS IN THE HISTORY OF SOCIAL SERVICES

Social services can trace its origin back to the idea of human goodwill and charity. Therefore, confining our study ofthis phenomenon to the modern era, and consequently ignoring its roots, would be a great error. However, forcenturies, charitable organizations of various sizes have been officially established. As a result of the incrediblediversity of such organizations in Islamic societies, conducting research in this field is also an easier task. There aremany examples of this institutional variety. For instance, the most notable examples would include the akhilik(fraternity) organisation, caravansary, almshouse, guilds, hospitals, charitable institutions, workhouses, Ottomanorphanages.Historically dervish lodges were mistakenly considered to be solely involved in mystic and esoteric activities.However, this Islamic religious order was fundamentally devoted to holy living through worldly deeds. Thisoriginates from the Sufi interpretation of religion, which revolved around serving; the creator, the lordly one trueGod, and his creations. As a result, the Sufis established Islamic monasteries (ribats), dervish lodge centres (hankah),small dervish lodges (zaviye), inns and bathhouses on deserted roads and mountain bases in order to provide freeaccommodation, to serve food and drink for cross border travellers and passers-by and generally to meet the needsof people. During the classical Ottoman period, they served as secondary cultural institutions, left vacant by thegovernment in city centres. They served as a meeting point between the political authorities and the people.Dervish lodges were sometimes a shelter for those seeking refuge from a state. We can also presume that theyreceived occupational therapy in the modern sense. This included training under the watchful eyes of the dhikr andcontemplation, for the purpose of serving humanity. As a result of their commitment to profession, diligence andthe use of logo therapy, they succeded in producing one of the most organised and effective historical instances ofsocial work. This study seeks to elucidate the historical role of dervish lodges in the provision of protective socialassistances, social aid and support from a social services stand point.

Assessing spatial interpolation based on sampling size and point geometry in elevation mapping applications


 
 
 
 In order to produce a correct elevation map, it is necessary to use not only the accurate technology for data acquisition, but also to utilize an appropriate method of interpolation, which will reflect the topographic features in a reliable manner. The first key element in elevation map production is the proper geometrical distribution of measurement points. The second key component is the density of measurement points, which indicates the distance between pairs in the dataset. In this study, two different types of sampling design were taken into account, random and systematic sampling, to create the elevation map. In random sampling, 33 points were used with the distance in the range of 15–30 km. In systematic sampling, a total of 100 points were utilized located at the distance of 5 km apart. Then, two distinct methods of interpolation were applied to produce a map: deterministic (Inverse Distance Weighting) and geostatistical (Ordinary Kriging with application of the Gaussian, Exponential, and Spherical fitting separately). These methods were compared using a statistical approach to validate the predictive abilities of the chosen interpolation methods. As the results showed, the geostatistical method, namely, Ordinary Kriging with Exponential fitting, revealed better performance compared to the deterministic. It was seen that the overall performance of the interpolated map varies with the number of points in the dataset and strongly relates to the sampling design. In the case of systematic sampling, the accuracy of the map was found to be much better compared to the results of random sampling. It was also proposed to use the error maps in order to identify areas with the maximum residuals. It became apparent that in the case of random sampling, the greatest errors were mostly concentrated in the areas where distances between the measured points were fairly large. By contrast, in the case of systematic sampling, the largest residuals were found in areas with complex topological patterns, especially in the regions with a steep slope gradient. Choosing the appropriate method of interpolation with the minimum error is of great importance in geostatistical operations and topographic engineering. Thus, the current manuscript may serve as a guideline in making the right decision concerning the interpolation method in elevation mapping applications of 1:2000000–1:1000000 scales.
 
 
 

Verilog HDL using LTE Implementation MAP Algorithm

In many communication systems, turbo coding Techniques for Encoding and Decoding are employed to repair errors. As compared to other error correction codes, turbo codes provide great error correcting capabilities. For the implementation of the Turbo decoder, a Very Large Scale Integration (VLSI) architecture is suggested in this study. The Maximum-a-Posteriori (MAP) algorithm is employed at the decoder side, where soft-in-soft-out decoders, interleaves, and deinterleavers are all used. The usage of the MAP algorithm reduces the quantity of iterations necessary to decode the information bits being transferred. This research employs a system for the encoder component that consists of two recursive convolutional encoders and a pseudorandom interleaver on the encoder side. Tools from Octave and Xilinx Vivado are used for the Turbo encoding and decoding. The system is synthesised and implemented using a specialised integrated circuit.

The Monitoring of Oxygen Saturation and Heart Rate Using a Telemedicine Smartphone System (TMSS) as a New Innovation in the Health Sector

As a country with the world's sixth-largest population with 11.22% poor population, Indonesia encounters health problems as one of the main issues. According to the Progress Report in Asia & the Pacific, Indonesia is still experiencing delays in the process of achieving the Millennium Development Goals. This study aimed to produce technological innovations related to the monitoring of oxygen saturation and heartbeat using the Telemedicine Smartphone System (TMSS). The contribution of this research is the resulting technological innovations related to the field of telemedicine that can be applied by Indonesian people at affordable prices. The monitoring tools will be effective and efficient when the tools are made with real-time monitoring of SpO2 and BPM using the TMSS system to improve Indonesia's development of health services. This design uses a fingertip sensor to detect oxygen saturation in the blood and an ear clip sensor to detect heartbeats, both sensors have an analog output which is conditioned in the Analog Signal Conditioning (ASC) circuit. The ASC’s output is processed on AT mega 328P. The resulting data is further displayed on the Liquid Character Display (LCD). Data are also sent via HC-05 Bluetooth and displayed on an Android Smartphone with SMS notifications. Based on the measurement results, the greatest error value was 0.220%, while the smallest was 0.055% on the SpO2. BPM had the largest error value of 2.33392%, while the smallest was 0.2283%. This research can be implemented into the transmission system using TMSS to improve the development of health services in Indonesia.

An improved numerical method for calculating mechanical properties of bi-modulus sandwich composite structures

Sandwich composite consists of panel material with higher strength and core material with lower strength, and the tensile elastic modulus and compressive modulus of these materials are often not equal. At present, the theoretical calculation and numerical calculation methods of bi-module materials are mainly applicable to single material and simple geometric structure, meanwhile, there will be situations such as slow convergence speed or even non-convergence of iterative algorithm. Therefore, when calculating sandwich composites, it is usually considered that the tensile modulus and compressive modulus are equal, which will bring great errors to the calculation. In order to better predict the cross-section characteristics and stiffness characteristics of bi-modulus sandwich composites, this paper developed the theoretical and numerical methods calculation methods suitable for bi-modulus sandwich composite structures. Example results show that the proposed finite element method based on field variables is consistent with the theoretical formula for bi-module materials, which can be used for structural design and safety check of marine sandwich composites.

Brain Response to a Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction and Controls.

Knee proprioception deficits and neuroplasticity have been indicated following injury to the anterior cruciate ligament (ACL). Evidence is, however, scarce regarding brain response to knee proprioception tasks and the impact of ACL injury. This study aimed to identify brain regions associated with the proprioceptive sense of joint position at the knee and whether the related brain response of individuals with ACL reconstruction differed from that of asymptomatic controls. Twenty-one persons with unilateral ACL reconstruction (mean 23 months post-surgery) of either the right (n = 10) or left (n = 11) knee, as well as 19 controls (CTRL) matched for sex, age, height, weight and current activity level, performed a knee joint position sense (JPS) test during simultaneous functional magnetic resonance imaging (fMRI). Integrated motion capture provided real-time knee kinematics to activate test instructions, as well as accurate knee angles for JPS outcomes. Recruited brain regions during knee angle reproduction included somatosensory cortices, prefrontal cortex and insula. Neither brain response nor JPS errors differed between groups, but across groups significant correlations revealed that greater errors were associated with greater ipsilateral response in the anterior cingulate (r = 0.476, P = 0.009), supramarginal gyrus (r = 0.395, P = 0.034) and insula (r = 0.474, P = 0.008). This is the first study to capture brain response using fMRI in relation to quantifiable knee JPS. Activated brain regions have previously been associated with sensorimotor processes, body schema and interoception. Our innovative paradigm can help to guide future research investigating brain response to lower limb proprioception.

EEG theta and N400 responses to congruent versus incongruent brand logos

Neuroimaging and behavioral studies have shown that brands convey meaning to consumers. To investigate the immediate reactions of the brain to brand logos, followed either by congruent or incongruent pictorial brand-related cues, can deepen understanding of the semantic processing of brands, and perhaps how consolidated the logo is in consumers’ minds. Participants were exposed to different brand-related image sets, that were either congruent (a match between brand-related images and brand logo) or incongruent (a mismatch between brand-related images and brand logo) while having their brain signals recorded. Event-related potential and EEG time–frequency domain features were extracted from the signals of the target image (brand logo). The results showed significantly larger N400 peak and relative theta power increase for incongruent compared to congruent logos, which could be attributed to an error-monitoring process. Thus, we argue that brands are encoded deeply in consumers’ minds, and cognitive processing of mismatched (vs matched) brand logos is more difficult, leading to greater error monitoring. The results were mostly consistent with previous studies investigating semantic incongruences in the linguistic field. Therefore, the error-monitoring process could be extended beyond linguistic forms, for example to images and brands.

Analiz izmeneniya koeffitsienta sherokhovatosti rusla maloi reki v zadannom stvore (na primere r. Chernoi) [Roughness coefficient meas-urements of the Chernaya River channel

The paper presents the determination of the roughness coefficient of the minor river channel, since one of the main design parameters depends on the minor stream, required for a substantiation of design decisions. In accordance with the regulatory documents of the Russian Federation, the roughness coefficient is taken according to the visual characteristics of the riverbed.The purpose of this work is to determine the relationship of the roughness coefficient and dimensionless complexes at different water depths (before and after entering the floodplain).All calculations are performed according to the results of studying the hydrological conditions of the Chernaya river. The roughness coefficient is determined by the numerical method.Analysis of the maximum depth allows to obtain its certain value. It is shown that the hydraulic radius increases at a higher depth. When the maximum depth is deeper, this dependence is nonmonotonic, and when water enters the floodplain, the hydraulic radius strongly differs from the average depth of the minor stream. It is found that before entering the floodplain, there is a significant stochastic relationship between the roughness coefficient, Reynolds number and the dimensionless complex. After entering the floodplain, there is a close stochastic relationship between roughness coefficient and the Froude number. When determining the minimum water levels, the exponent of Chezy's velocity factor in the Manning formula cannot be considered a constant value, because this can lead to a great error.

The Influence of Muscular Strength and Local Muscular Endurance on Accuracy of Estimated Repetitions to Failure in Resistance-Trained Males.

This study investigated whether muscular strength and local muscular endurance (LME) influences accuracy of estimated repetitions to failure (ERF) during resistance exercise. Twenty resistance-trained males (age 26.3 ± 6.9 years) completed five sets of 10 repetitions at 70% 1RM for the bench press and squat. Following the 10th repetition of each set, participants reported ERF and then continued to concentric failure. Participants were separated into one of two groups based on muscular strength and LME. There were no significant differences between strength groups for error in ERF, ERF, and actual repetitions to failure (ARF). High-LME compared to Low-LME had greater ERF for all sets of bench press (p < 0.05) and two sets of squat (p < 0.05). Greater ARF was observed in High-LME for two of five sets for bench press (p < 0.05) and squat (p < 0.05). High-LME had greater error in ERF for bench press set 1 (p < 0.01) and set 4 (p = 0.04), while for set 1 only for squat (p = 0.01). Findings indicate that LME influences accuracy of ERF during the initial set of bench press and squat as well as a latter set for the bench press. Future studies with larger sample sizes are warranted to explore whether LME affects accuracy of ERF across multiple sets.

Culling Double Counting in Sequence Images for Fruit Yield Estimation

Exact yield estimation of fruits on plants guaranteed fine and timely decisions on harvesting and marketing practices. Automatic yield estimation based on unmanned agriculture offers a viable solution for large orchards. Recent years have witnessed notable progress in computer vision with deep learning for yield estimation. Yet, the current practice of vision-based yield estimation with successive frames may engender fairly great error because of the double counting of repeat fruits in different images. The goal of this study is to provide a wise framework for fruit yield estimation in sequence images. Specifically, the anchor-free detection architecture (CenterNet) is utilized to detect fruits in sequence images from videos collected in the apple orchard and orange orchard. In order to avoid double counts of a single fruit between different images in an image sequence, the patch matching model is designed with the Kuhn–Munkres algorithm to optimize the paring process of repeat fruits in a one-to-one assignment manner for the sound performance of fruit yield estimation. Experimental results show that the CenterNet model can successfully detect fruits, including apples and oranges, in sequence images and achieved a mean Average Precision (mAP) of 0.939 under an IoU of 0.5. The designed patch matching model obtained an F1-Score of 0.816 and 0.864 for both apples and oranges with good accuracy, precision, and recall, which outperforms the performance of the reference method. The proposed pipeline for the fruit yield estimation in the test image sequences agreed well with the ground truth, resulting in a squared correlation coefficient of R2apple = 0.9737 and R2orange = 0.9562, with a low Root Mean Square Error (RMSE) for these two varieties of fruit.

Interindividual differences influence multisensory processing during spatial navigation.

When moving through space, we encode multiple sensory cues that guide our orientation through the environment. The integration between visual and self-motion cues is known to improve navigation. However, spatial navigation may also benefit from multisensory external signals. The present study aimed to investigate whether humans combine auditory and visual landmarks with improving their navigation abilities. Two experiments with different cue reliability were conducted. In both, participants' task was to return an object to its original location by using landmarks, which could be visual-only, auditory-only, or audiovisual. We took error and variability of object relocation distance as measures of accuracy and precision. To quantify interference between cues and assess their weights, we ran a conflict condition with a spatial discrepancy between visual and auditory landmarks. Results showed comparable accuracy and precision when navigating with visual-only and audiovisual landmarks but greater error and variability with auditory-only landmarks. Splitting participants into two groups based on given unimodal weights revealed that only subjects who associated similar weights to auditory and visual cues showed precision benefit in audiovisual conditions. These findings suggest that multisensory integration occurs depending on idiosyncratic cue weighting. Future multisensory procedures to aid mobility must consider individual differences in encoding landmarks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Accuracy of patient setup positioning using surface-guided radiotherapy with deformable registration in cases of surface deformation.

The Catalyst™ HD (C‐RAD Positioning AB, Uppsala, Sweden) is surface‐guided radiotherapy (SGRT) equipment that adopts a deformable model. The challenge in applying the SGRT system is accurately correcting the setup error using a deformable model when the body of the patient is deformed. This study evaluated the effect of breast deformation on the accuracy of the setup correction of the SGRT system. Physical breast phantoms were used to investigate the relationship between the mean deviation setup error obtained from the SGRT system and the breast deformation. Physical breast phantoms were used to simulate extension and shrinkage deformation (−30 to 30 mm) by changing breast pieces. Three‐dimensional (3D) Slicer software was used to evaluate the deformation. The maximum deformations in X, Y, and Z directions were obtained as the differences between the original and deformed breasts. We collected the mean deviation setup error from the SGRT system by replacing the original breast part with the deformed breast part. The mean absolute difference of lateral, longitudinal, vertical, pitch, roll, and yaw, between the rigid and deformable registrations was 2.4 ± 1.7 mm, 1.3 ± 1.2 mm, 6.4 ± 5.2 mm, 2.5° ± 2.5°, 2.2° ± 2.4°, and 1.0° ± 1.0°, respectively. Deformation in the Y direction had the best correlation with the mean deviation translation error (R = 0.949) and rotation error (R = 0.832). As the magnitude of breast deformation increased, both mean deviation setup errors increased, and there was greater error in translation than in rotation. Large deformation of the breast surface affects the setup correction. Deformation in the Y direction most affects translation and rotation errors.