Target Error Research Articles

MVCT versus kV-CBCT for targets subject to respiratory motion: A phantom study.

The use of kilovoltage cone‐beam computed tomography (kV‐CBCT) or megavoltage computed tomography (MVCT) for image guidance prior to lung stereotactic body radiation therapy (SBRT) is common clinical practice. We demonstrate that under equivalent respiratory conditions, image guidance using both kV‐CBCT and MVCT may result in the inadequate estimation of the range of target motion under free‐breathing (FB) conditions when standard low‐density window and levels are used. Two spherical targets within a respiratory motion phantom were imaged using both long‐exhale (LE) and sinusoidal respiratory traces. MVCT and kV‐CBCT images were acquired and evaluated for peak‐to‐peak amplitudes of 10 or 20 mm in the cranial‐caudal direction, and with 2, 4 or 5 s periods. All images were visually inspected for artifacts and conformity to the ITV for each amplitude, period, trace‐type, and target size. All LE respiratory traces required a lower threshold HU window for MVCT and kV‐CBCT compared to sinusoidal traces to obtain 100% volume conformity compared with the theoretical ITV (ITVT). Excess volume was less than 2% for all kV‐CBCT contours regardless of trace‐type, breathing period, or amplitude, while the maximum excess volume for MVCT was 48%. Adjusting window and level to maximize conformity with the ITVT is necessary to reduce registration uncertainty to less than 5 mm. To fully capture target motion with either MVCT or kV‐CBCT, substantial changes in HU levels up to −600 HU are required which may not be feasible clinically depending on the target's location and surrounding tissue contrast. This registration method, utilizing a substantially decreased window and level compared to standard low‐density settings, was retrospectively compared to the automated registration algorithm for five lung SBRT patients exposed to pre‐treatment kV‐CBCT image guidance. Differences in registrations in the super‐inferior (SI) direction greater than the commonly used ITV to PTV margin of 5 mm were encountered for several cases. In conclusion, pre‐treatment image guidance for lung SBRT targets using MVCT or kV‐CBCT is unlikely to capture the full extent of target motion as defined by the ITVT and additional caution is warranted to avoid registration errors for small targets and patients with LE respiratory traces.

Exact Properties of Some Heteroscedastic TOST Alternatives for Bioequivalence

ABSTRACT The two one-sided tests (TOST) procedure is the common method for assessing bioequivalence between two different drugs or formulations of the same drug. Several solutions to Behrens-Fisher problem have been extended to establish statistical equivalence under variance heterogeneity. Unlike other existing studies that rely exclusively on simulation results, the analytical formulas of power and Type I error rate are derived. Exact numerical investigations were conducted to evaluate the behavior of the Welch–Satterthwaite, Cochran–Cox, and Banerjee–McCullough TOST methods. The results show that the Type I error rates of the Cochran–Cox and Banerjee–McCullough tests never exceed the nominal significance level. The Banerjee–McCullough technique is actually more conservative than the Cochran–Cox procedure. The extended Welch–Satterthwaite approach maintains closest to the preassigned significance level and is almost equal to the target error probability. The exact power levels of the Cochran–Cox and Banerjee–McCullough tests are completely or nearly identical, and are always less than that of the Welch–Satterthwaite method. On the basis of excellent control of Type I error and greater power performance, the extended Welch–Satterthwaite procedure is recommended over the other two heteroscedastic TOST methods. These findings provide an update of previous studies that endorse the somehow inferior Banerjee–McCullough method.

Effect of dual aircraft formation spacing on target position tracking on measurement conversion by monopulse radar

Aimed at the current problem of insufficient analysis of the influence of the diversified formation of dual aircraft on monopulse radar position tracking, the dual aircraft echo equivalent two point source jamming model is built. We designed the dual aircraft formation penetration movement scenario and three different formation spacings of 150, 250, and 350 m and extracted the dynamic radar cross section sequences of dual aircraft under different formation spacings. We established the dual aircraft formation equivalent scenario and calculated the dynamic signal-to-noise ratio and distance measurement accuracy of the radar received echo signals with different formation spacings. We fully considered the randomness characteristics of the phase difference of the actual dual aircraft echo and built the random angle error model of dual aircraft echo equivalent jamming. The distribution and random numerical characteristics of the random angular error are simulated and analyzed, and we combined the radar measurement conversion target position tracking algorithm to analyze the influence of different formation spacings on the monopulse radar tracking target position and position tracking accuracy. The simulation results show that a formation spacing of 350 m produces a greater randomness of angular error for dual targets, resulting in a greater dispersion of radar measurement traces, and the final average position mean square error is 132.8 m, which improves the position error by 15.6% compared with 150 m spacing.

Gaze Accuracy Differences During Single-Leg Balance Following Anterior Cruciate Ligament Reconstruction.

Individuals following anterior cruciate ligament reconstruction (ACLR) demonstrate altered postural stability and functional movement patterns. It is hypothesized that individuals following ACLR may compensate with sensory adaptations with greater reliance on visual mechanisms during activities. It is unknown if visual compensatory strategies are implemented to maintain postural stability during functional tasks. To examine visual gaze accuracy during a single-leg balance task in individuals following ACLR compared with healthy, active controls. Case control. Controlled laboratory. A total of 20 individuals (10 ACLR and 10 healthy controls) participated in the study. Visual gaze patterns were obtained during 20-second single-leg balance trials while participants were instructed to look at presented targets. During the Stationary Target Task, the visual target was presented in a central location for the duration of the trial. The Moving Target Task included a visual target that randomly moved to 1 of 9 target locations for a period of 2 seconds. Targets were stratified into superior, middle, and inferior levels for the Moving Target Task. The Stationary Target Task demonstrated no differences in visual error between groups (P = .89). The Moving Target Task demonstrated a significant interaction between group and target level (F2,36 = 3.76, P = .033). Individuals following ACLR demonstrated greater visual error for the superior targets (ACLR = .70 [.44]m, healthy = .41 [.21]m, Cohen d = 0.83 [0.06 to 1.60]) and inferior targets (ACLR = .68 [.25]m, healthy = .33 [.16]m, Cohen d = 1.67 [0.81 to 2.52]). Individuals following ACLR demonstrate greater visual error during settings of high or low visual stimuli compared with healthy individuals to maintain single-limb postural stability. This population may rely on visual input to compensate for the somatosensory changes following injury.

Abstract 3070: Lung cancer TTFields treatment planning sensitivity to errors in torso segmentation

Abstract Introduction: Tumor Treating Fields (TTFields) is a treatment modality for glioblastoma multiforme (GBM) and other malignant tumors, utilizing low-intensity, intermediate frequency (100-300kHz) alternating electric field delivered through noninvasive transducer arrays. TTFields are currently being tested in a phase III clinical trial for the treatment of advanced Non-Small Cell Lung Cancer (NSCLC). Previous studies have demonstrated that the treatment efficacy increases when the dose of TTFields delivered to the tumor is at least 1 V/cm. Thus, personalized simulations to estimate the dose are performed as part of the patient treatment planning. For NSCLC treatment, these simulations require the segmentation of torso tissues. We are currently developing a semi-automatic software for the segmentation of these tissues. Achieving highly accurate segmentation is time consuming and not always necessary. Therefore, in this study we assess the level of segmentation accuracy that is required for TTFields dose estimation. Methods: We introduce a novel pipeline for evaluating the sensitivity of TTFields treatment planning errors in the segmentation of torso tissues. To this end, we incorporated an expert-segmented torso volume and artificially placed NSCLC tumors of different sizes in the vicinity of the tested torso tissue. We employed relaxations to the segmentation algorithm and derived the TTFields distribution with and without the simulated segmentation errors. We then computed the treatment planning error as the per-voxel average deviation of the TTFields dose computed over the erroneous segmentation from the reference one. The dose was calculated over the simulated tumor location and over the entire lung volume. Results: We have evaluated our sensitivity analysis pipeline on 9 different test cases. Based on previous analysis, we have set our tolerable target error to be 0.1 V/cm. Our results show that 6 out of the 9 tests were within the target, whereas the other 3 exceeded the target, requiring algorithmic refinements. Conclusions: We have presented a method for estimating the sensitivity of lung cancer TTFields treatment planning to segmentation errors. This method is used to evaluate the required accuracy of the semi-automatic torso segmentation tool that we are currently developing. Our method can be further extended to other types of tumors in different regions of the body. Citation Format: Hadas Ben Atya, Oren Peles, Reuben Shamir, Zeev Bomzon. Lung cancer TTFields treatment planning sensitivity to errors in torso segmentation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3070.

The effects of target size and error rate on the cognitive demand and stress during augmented reality interactions

This study investigated the effects of target size and error rate on cognitive demand during augmented reality (AR) interactions. In a repeated-measures laboratory study, twenty participants performed two AR tasks (omni-directional pointing and cube placing) with different target sizes and error rates. During the AR tasks, we measured cerebral oxygenation using functional near-infrared spectroscopy (fNIRS), perceived workload using the NASA-TLX questionnaire, stress using the Short Stress State Questionnaire, and task performance (task completion time). The results showed that the AR tasks with more interaction errors increased cerebral oxygenation, perceived workload, and task completion time while the target size significantly affected physical demand and task completion time. These results suggest that appropriate target sizes and low system errors may reduce potential cognitive demand in AR interactions.

Unmanned aerial vehicle reconnaissance image recognition based on convolutional neural network

The important strategic position of military UAVs and the wide application of civil UAVs in many fields, they all mark the arrival of the era of unmanned aerial vehicles. At present, in the field of image research, recognition and real-time tracking of specific objects in images has been a technology that many scholars continue to study in depth and need to be further tackled. Image recognition and real-time tracking technology has been widely used in UAV aerial photography. Through the analysis of convolution neural network algorithm and the comparison of image recognition technology, the convolution neural network algorithm is improved to improve the image recognition effect. In this paper, a target detection technique based on improved Faster R-CNN is proposed. The algorithm model is implemented and the classification accuracy is improved through Faster R-CNN network optimization. Aiming at the problem of small target error detection and scale difference in aerial data sets, this paper designs the network structure of RPN and the optimization scheme of related algorithms. The structure of Faster R-CNN is adjusted by improving the embedding of CNN and OHEM algorithm, the accuracy of small target and multitarget detection is improved as a whole. The experimental results show that: compared with LENET-5, the recognition accuracy of the proposed algorithm is significantly improved. And with the increase of the number of samples, the accuracy of this algorithm is 98.9%.

The Magnetic Resonance Imaging (MRI)-Directed Implantable Guide Tube Technique: Accuracy and Applications in Deep Brain Stimulation

The magnetic resonance imaging (MRI)-directed implantable guide tube technique allows for direct targeting of deep brain structures without microelectrode recording or intraoperative clinical assessment. This study describes a 10-year institutional experience of this technique including nuances that enable performance of surgery using readily available equipment. Eighty-seven patients underwent deep brain stimulation surgery using the guide tube technique for Parkinson disease (n= 59), essential tremor (n= 16), and dystonia (n= 12). Preoperative and intraoperative MRI was analyzed to measure lead accuracy, volume of pneumocephalus, and the ability to safely plan a trajectory for multiple electrode contacts. Mean target error was measured to be 0.7 mm (95% confidence interval [CI] 0.6-0.8 mm) in the anteroposterior plane, 0.6 mm (95% CI 0.5-0.7 mm) in the mediolateral plane, and 0.8 mm (95% CI 0.7-0.9 mm) in the superoinferior plane. Net deviation (Euclidean error) from the planned target was 1.3 mm (95% CI 1.2-1.4 mm). Mean intracranial air volume per lead was 0.2 mL (95% CI 0.1-0.4 mL). In total, 52 patients had no intracranial air on postoperative imaging. In all patients, a safe trajectory could be planned to target for multiple electrode contacts without violating critical neural structures, the lateral ventricle, sulci, or cerebral blood vessels. The MRI-directed implantable guide tube technique is a highly accurate, low-cost, reliable method for introducing deep brain electrodes. This technique reduces brain shift secondary to pneumocephalus and allows for whole trajectory planning of multiple electrode contacts.

URLLC With Massive MIMO: Analysis and Design at Finite Blocklength

The fast adoption of Massive MIMO for high-throughput communications was enabled by many research contributions mostly relying on infinite-blocklength information-theoretic bounds. This makes it hard to assess the suitability of Massive MIMO for ultra-reliable low-latency communications (URLLC) operating with short-blocklength codes. This paper provides a rigorous framework for the characterization and numerical evaluation (using the saddlepoint approximation) of the error probability achievable in the uplink and downlink of Massive MIMO at finite blocklength. The framework encompasses imperfect channel state information, pilot contamination, spatially correlated channels, and arbitrary linear spatial processing. In line with previous results based on infinite-blocklength bounds, we prove that, with minimum mean-square error (MMSE) processing and spatially correlated channels, the error probability at finite blocklength goes to zero as the number <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> of antennas grows to infinity, even under pilot contamination. However, numerical results for a practical URLLC network setup involving a base station with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M=100$ </tex-math></inline-formula> antennas, show that a target error probability of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−5</sup> can be achieved with MMSE processing, uniformly over each cell, only if orthogonal pilot sequences are assigned to all the users in the network. Maximum ratio processing does not suffice.

A measurement error Rao\u2013Yu model for regional prevalence estimation over time using uncertain data obtained from dependent survey estimates

The assessment of prevalence on regional levels is an important element of public health reporting. Since regional prevalence is rarely collected in registers, corresponding figures are often estimated via small area estimation using suitable health data. However, such data are frequently subject to uncertainty as values have been estimated from surveys. In that case, the method for prevalence estimation must explicitly account for data uncertainty to allow for reliable results. This can be achieved via measurement error models that introduce distribution assumptions on the noisy data. However, these methods usually require target and explanatory variable errors to be independent. This does not hold when data for both have been estimated from the same survey, which is sometimes the case in official statistics. If not accounted for, prevalence estimates can be severely biased. We propose a new measurement error model for regional prevalence estimation that is suitable for settings where target and explanatory variable errors are dependent. We derive empirical best predictors and demonstrate mean-squared error estimation. A maximum likelihood approach for model parameter estimation is presented. Simulation experiments are conducted to prove the effectiveness of the method. An application to regional hypertension prevalence estimation in Germany is provided.

Electromanyetik Silahlı Terörle Mücadele Robotu

This article proposes the integration of electromagnetic weapons on a robot, design and construction of an electromagnetic armed robot, autonomous targeting of possible targets with the electromagnetic weapon, and the features a electromagnetic armed safety robot should have. Unlike traditional user-targeted field security robot approaches, the robot mentioned in this study detects potential threats in the task area with image processing and artificial intelligence techniques, so the user can accurately identify and autonomously target targets without the need for controlled targeting. Unlike today’s armed robots, an electromagnetic armed robot, which will be a new literature study, has been developed to create a reference path. An electromagnetic weapon that can be carried by a robot is produced and integrated into the robot and a new armed robot approach with electromagnetic weapon is introduced. Various methods are proposed considering the range restriction of electromagnetic weapons and possible targeting errors of the robot user. A control algorithm has been developed to have the most appropriate targeting under the dynamic constraints of the robot and user for target tracking. Prototyping and experiments show the ability of an autonomous security robot with an autonomous targeting system to troubleshoot user problems and targeting problems. In addition, various methods and recommendations are provided for the features that a electromagnetic armed security robot working in the field should have.

Optimization of The Backpropagation Method with Nguyen-widrow in Face Image Classification

In this study, it is proven that the Nguyen-widrow algorithm can optimize the Backpropagation method in terms of initializing weights and bias. With the Nguyen-widrow algorithm, the Backpropagation method can recognize facial images faster with better accuracy. In the testing process with hidden layer 6 neurons, at a target error of 0.01, the standard Backpropagation method obtained an accuracy of 96%, while the optimization Backpropagation method obtained a higher accuracy of 98%. So on with hidden layers 7, 8, 9, and 10 neurons. then in other words this research can be used to advance human technology in facilitating all aspects of life with these algorithms and methods. With the accuracy and speed of capturing facial images, this can be used as policy like a surveillance camera, traffic protection, and many other things that can be used in social life.

Multi-objective drilling trajectory optimization using decomposition method with minimum fuzzy entropy-based comprehensive evaluation

This paper is concerned with the optimization problem of drilling trajectory design, which plays a vital role in ensuring the safety and enhancing the efficiency of an industrial drilling process. Due to complex geological environment and limited capacity of equipment, the problem to be addressed features multi-objective and multi-constraint, and consists of two challenges: (1) how to formulate a proper optimization scheme and efficiently solve it for a group of solutions; and (2) how to pick out a desired result from the obtained Pareto solutions according to certain requirements. In this paper, to meet drilling practice, three objective functions are introduced regarding trajectory length, well-profile energy, and target error, respectively. Constraints are the range of decision parameters, non-negative constraints and bound of the target area. As a result, a comprehensive optimization model for the design of drilling trajectory is established. A novel optimization algorithm is devised to deal with the contradictory objectives and multiple nonlinear constraints, which combines an adaptive penalty function with multi-objective evolutionary algorithm based on decomposition. A fuzzy-entropy-based evaluation approach is further employed to determine a satisfactory solution from the group of obtained ones. A case study illustrates that (1) our optimization solution is indeed beneficial to the optimization of drilling trajectory; and (2) the optimization algorithm and the decision method therein outperform some existing ones, which shows both practical and theoretical significance.

Hierarchical motor adaptations negotiate failures during force field learning.

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of 'internal model adaptation'. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

Speech auditory-motor adaptation to formant-shifted feedback lacks an explicit component: Reduced adaptation in adults who stutter reflects limitations in implicit sensorimotor learning.

The neural mechanisms underlying stuttering remain poorly understood. A large body of work has focused on sensorimotor integration difficulties in individuals who stutter, including recently the capacity for sensorimotor learning. Typically, sensorimotor learning is assessed with adaptation paradigms in which one or more sensory feedback modalities are experimentally perturbed in real time. Our own previous work on speech with perturbed auditory feedback revealed substantial auditory-motor learning limitations in both children and adults who stutter (AWS). It remains unknown, however, which subprocesses of sensorimotor learning are impaired. Indeed, new insights from research on upper limb motor control indicate that sensorimotor learning involves at least two distinct components: (a) an explicit component that includes intentional strategy use and presumably is driven by target error and (b) an implicit component that updates an internal model without awareness of the learner and presumably is driven by sensory prediction error. Here, we attempted to dissociate these components for speech auditory-motor learning in AWS versus adults who do not stutter (AWNS). Our formant-shift auditory-motor adaptation results replicated previous findings that such sensorimotor learning is limited in AWS. Novel findings are that neither control nor stuttering participants reported any awareness of changing their productions in response to the auditory perturbation and that neither group showed systematic drift in auditory target judgments made throughout the adaptation task. These results indicate that speech auditory-motor adaptation to formant-shifted feedback relies exclusively on implicit learning processes. Thus, limited adaptation in AWS reflects poor implicit sensorimotor learning. Speech auditory-motor adaptation to formant-shifted feedback lacks an explicit component: Reduced adaptation in adults who stutter reflects limitations in implicit sensorimotor learning.

Towards Tracking of Deep Brain Stimulation Electrodes Using an Integrated Magnetometer.

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

Adaptive Coding and Bit-Power Loading Algorithms for Underwater Acoustic Transmissions

Underwater acoustic channel (UAC) is featured as fast time-varying characteristic, and challenges the transmission designs. To countermine the time variation effect, we propose an adaptive design for orthogonal frequency division multiplexing (OFDM) transmission systems by utilizing the long-term stability of the second-order statistics of the channel state information (CSI). We derive the analytical expression of signal-to-interference-plus-noise-ratio (SINR) at each subcarrier to reach the target error performance based on the statistical information of the CSI. Thereafter, a new adaptive coding and bit-power loading algorithm with low computational complexity is proposed to pursuit the highest achievable bit rate with fixed error rate. The validity of SINR calculations and the effectiveness of the proposed adaptive algorithm are demonstrated under various conditions, wherein both simulated and measured channels have been tested.

A runtime based comparison of highly tuned lattice Boltzmann and finite difference solvers

The aim of this work is a fair and unbiased comparison of a lattice Boltzmann method (LBM) against a finite difference method (FDM) for the simulation of fluid flows. Rather than reporting metrics such as floating point operation rates or memory throughput, our work considers the engineering quest of reaching a desired solution quality with the least computational effort. The specific lattice Boltzmann and finite difference methods selected here are of a very basic nature to emphasize the influence of the fundamentally different approaches. To minimize the skew in the measurements, complex boundary condition schemes and further advanced techniques are avoided and instead both methods are fully explicit, weakly compressible approaches. Due to the highly optimized nature of both codes, different sets of restrictions are imposed by either method. Using the common set of features, two relatively simple test cases in terms of a duct flow and the flow in a lid driven cavity are considered and are tuned to perform optimally with both approaches. As a third test case, a transient flow around a square cylinder is used to demonstrate the applicability to engineering oriented settings and in a temporal domain. The performance of the two methods is found to be very similar with no full advantage for any of the approaches. Overall a tendency toward better performance of the LBM at larger target errors and for indirect benchmark quantities, such as lift and drag, is observed, while the FDM excels at smaller target errors and direct comparisons of velocity and pressure profiles to analytical solutions. Other factors such as the difficulty of setting consistent boundary conditions in the LBM or the effect of stabilization in the FDM are likely to be the most important criteria when searching for a very fast flow solver for practical applications.

Passive Ranging Based on Accurate Prediction of Target Radiation Temperature

In this paper, a passive ranging method based on accurate prediction of target radiation temperature is proposed. Firstly, different wave bands are intercepted and the corresponding light radiation energy on two different wave bands are obtained; secondly, the temperature of target is estimated according to the linear relationship of the corresponding light radiation energy in two different wave bands; and the target can be equivalent to a blackbody of different temperature categories; thus, the range information of the target can be obtained, and the passive ranging error of air target can be realized. In this way, the target can be divided into different categories according to its own temperature, and the subspace of passive ranging can be effectively divided, which can provide a rule to avoid blindness for the subsequent target distance estimation. In the end of this paper, the accuracy of the method is verified by experiments, and the error of ranging accuracy is analyzed, which proves the feasibility of this method, and lays a foundation for future engineering applications.

Hidden Error in Optical Stereotactic Navigation Systems and Strategy to Maximize Accuracy

Background: Optical neuronavigation has been established as a reliable and effective adjunct to many neurosurgical procedures. Operations such as asleep deep brain stimulation (aDBS) benefit from the potential increase in accuracy that these systems offer. Built into these technologies is a degree of tolerated error that may exceed the presumed accuracy resulting in suboptimal outcomes. Objective: The objective of this study was to identify an underlying source of error in neuronavigation and determine strategies to maximize accuracy. Methods: A Medtronic Stealth system (Stealth Station 7 hardware, S8 software, version 3.1.1) was used to simulate an aDBS procedure with the Medtronic Nexframe system. Multiple configurations and orientations of the Nexframe-Nexprobe system components were examined to determine potential sources of, and to quantify navigational error, in the optical navigation system. Virtual entry point and target variations were recorded and analyzed. Finally, off-plan error was recorded with the AxiEM system and visual observation on a phantom head. Results: The most significant source of error was found to be the orientation of the reference marker plate configurations to the camera system, with the presentation of the markers perpendicular to the camera line of site being the most accurate position. Entry point errors ranged between 0.134 ± 0.048 and 1.271 ± 0.0986 mm in a complex, reproducible pattern dependent on the orientation of the Nexprobe reference plate. Target errors ranged between 0.311 ± 0.094 and 2.159 ± 0.190 mm with a similarly complex, repeatable pattern. Representative configurations were tested for physical error at target with errors ranging from 1.2 mm to 1.4 mm. Throughout data acquisition, no orientation was indicated as outside the acceptable tolerance by the Stealth software. Conclusions: Use of optical neuronavigation is expected to increase in frequency and variety of indications. Successful implementation of this technology depends on understanding the tolerances built into the system. In situations that depend on extremely high precision, surgeons should familiarize themselves with potential sources of error so that systems may be optimized beyond the manufacturer’s built-in tolerances. We recommend that surgeons align the navigation reference plate and any optical instrument’s reference plate spheres in the plane perpendicular to the line of site of the camera to maximize accuracy.