Mm Of Error Research Articles

Validation of three-dimensional facial imaging captured with smartphone-based photogrammetry application in comparison to stereophotogrammetry system

Statement of problemThe development of facial scanners has improved capabilities to create three-dimensional (3D) virtual patients for accurate facial and smile analysis. However, most of these scanners are expensive, stationary and involve a significant clinical footprint. The use of the Apple iPhone and its integrated “TrueDepth” near-infrared (NIR) scanner combined with an image processing application (app) offers the potential to capture and analyze the unique 3D nature of the face; the accuracy and reliability of which are yet to be established for use in clinical dentistry. PurposeThis study was designed to validate both the trueness and precision of the iPhone 11 Pro smartphone TrueDepth NIR scanner in conjunction with the Bellus3D Face app in capturing 3D facial images in a sample of adult participants in comparison to the conventional 3dMDface stereophotogrammetry system. Material and methodsTwenty-nine adult participants were prospectively recruited. Eighteen soft tissue landmarks were marked on each participant's face before imaging. 3D facial images were captured using a 3dMDface system and the Apple iPhone TrueDepth NIR scanner combined with the Bellus3D Face app respectively. The best fit of each experimental model to the 3dMD scan was analyzed using Geomagic Control X software. The root mean square (RMS) was used to measure the “trueness” as the absolute deviation of each TrueDepth scan from the reference 3dMD image. Individual facial landmark deviations were also assessed to evaluate the reliability in different craniofacial regions. The “precision” of the smartphone was tested by taking 10 consecutive scans of the same subject and comparing those to the reference scan. Intra-observer and inter-observer reliabilities were assessed using the intra-class correlation coefficient (ICC). ResultsRelative to the 3dMDface system, the mean RMS difference of the iPhone/Bellus3D app was 0.86 ± 0.31 mm. 97% of all the landmarks were within 2 mm of error compared with the reference data. The ICC for intra-observer reproducibility or precision of the iPhone/Bellus3D app was 0.96, which was classified as excellent. The ICC for inter-observer reliability was 0.84, which was classified as good. ConclusionsThese results suggest that 3D facial images acquired with this system, the iPhone TrueDepth NIR camera in conjunction with the Bellus3D Face app, are clinically accurate and reliable. Judicious use is advised in clinical situations that require high degrees of detail due to a lack of image resolution and a longer acquisition time. Generally, this system possesses the potential to serve as a practical alternative to conventional stereophotogrammetry systems for use in a clinical setting due to its accessibility and relative ease of use and further research is planned to appraise its updated clinical use.

Localization of deep brain stimulation trajectories via automatic mapping of microelectrode recordings to MRI

Objective. Suboptimal electrode placement during subthalamic nucleus deep brain stimulation (STN DBS) surgery may arise from several sources, including frame-based targeting errors and intraoperative brain shift. We present a computer algorithm that can accurately localize intraoperative microelectrode recording (MER) tracks on preoperative magnetic resonance imaging (MRI) in real-time, thereby predicting deviation between the surgical plan and the MER trajectories. Approach. Random forest (RF) modeling was used to derive a statistical relationship between electrophysiological features on intraoperative MER and voxel intensity on preoperative T2-weighted MR imaging. This model was integrated into a larger algorithm that can automatically localize intraoperative MER recording tracks on preoperative MRI in real-time. To verify accuracy, targeting error of both the planned intraoperative trajectory (‘planned’) and the algorithm-derived trajectory (‘calculated’) was estimated by measuring deviation from the final DBS lead location on postoperative high-resolution computed tomography (‘actual’). Main results. MR imaging and MERs were obtained from 24 STN DBS implant trajectories. The cross-validated RF model could accurately distinguish between gray and white matter regions along MER trajectories (AUC 0.84). When applying this model within the localization algorithm, the calculated MER trajectory estimate was found to be significantly closer to the actual DBS lead when compared to the planned trajectory recorded during surgery (1.04 mm vs 1.52 mm deviation, p < 0.002), with improvement shown in 19/24 cases (79%). When applying the algorithm to simulated DBS trajectory plans with randomized targeting error, up to 4 mm of error could be resolved to <2 mm on average (p < 0.0001). Significance. This work presents an automated system for intraoperative localization of electrodes during STN DBS surgery. This neuroengineering solution may enhance the accuracy of electrode position estimation, particularly in cases where high-resolution intraoperative imaging is not available.

Optimization of reconstruction time of ultrasound computed tomography with a piecewise homogeneous region-based refract-ray model

In this article, a novel ultrasound computed tomography (USCT) reconstruction algorithm for breast imaging is proposed. This algorithm is based on an ultrasound propagation model, the refract-ray model (RRM). In this model, the field of imaging is assumed as piecewise homogenous and is divided into several regions. The ultrasound propagation paths are considered polylines that only refract at the borders of the regions. The edge information is provided by B-mode imaging. Both simulations and experiments are implemented to validate the proposed algorithm. Compared with the traditional bent-ray model (BRM), the time of reconstructions using RRM decreases by over 90 %. In simulations, the imaging qualities for RRM and BRM are comparable, in terms of the root mean square error, the Tenengrad value, and the deformation of digital phantom. In the experiments, a cylindrical agar phantom is imaged using a customized imaging system. When imaging using RRM, the estimate of the phantom radius is about 0.1 mm in error, while it is about 0.3 mm in error using BRM. Moreover, the Tenengrad value of the result using RRM is much higher than that using BRM (9.76 compared to 0.79). The results show that the proposed algorithm can better delineate the phantom within a water bath. In future work, further experimental work is required to validate the method for improving imaging quality under breast-mimicking imaging conditions.

John Charnley Award: Deep Learning Prediction of Hip Joint Center on Standard Pelvis Radiographs.

Accurate hip joint center (HJC) determination is critical for preoperative planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and commonly used classification systems in primary and revision hip replacement. However, current methods of preoperative HJC estimation are prone to subjectivity and human error. The purpose of the study was to leverage deep learning (DL) to develop a rapid and objective HJC estimation tool on anteroposterior (AP) pelvis radiographs. Radiographs from 3,965 patients (7,930 hips) were included. A DL model workflow was created to detect bony landmarks and estimate HJC based on a pelvic height ratio method. The workflow was utilized to conduct a grid-search for optimal nonspecific, sex-specific, and patient-specific (using contralateral hip) pelvic height ratios on the training/validation cohort (6,344 hips). Algorithm performance was assessed on an independent testing cohort for HJC estimation comparison. The algorithm estimated HJC for the testing cohort at a rate of 0.65 seconds/hip based on features in AP radiographs alone. The model predicted HJC within 5 mm of error for 80% of hips using nonspecific ratios, which increased to 83% with sex-specific and 91% with patient-specific pelvic height ratio models. Mean error decreased utilizing the patient-specific model (3.09 ± 1.69 mm, P < .001). Using DL, we developed nonspecific, sex-specific, and patient-specific models capable of estimating native HJC on AP pelvis radiographs. This tool may provide clinical value when considering preoperative component position in patients planned to undergo THA and in reducing the subjective variability in HJC estimation. Diagnostic, level IV.

A Virtual-Reality Imaging Analysis of the Dynamic Aortic Root Anatomy

PurposeTo measure and explore complex cardiac anatomy in research and preoperative simulation, a virtual imaging technology—the Vesalius 3D suite (PS Medtech, Amsterdam, Netherlands)—combines Vesalius three-dimensional (3D) image-processing software with an optic-tracking navigation system running PST-Client software. We present a novel method of evaluating dynamic aortic root geometry in vivo using this visualization system. DescriptionBased on electrocardiography-gated cardiac computed tomography data in systole and diastole, images of the aortic root in a healthy adult were reconstructed for 3D visualization. Virtual interaction tools were used to explore and measure the aortic root structures. EvaluationVirtually reconstructed images revealed the aortic root internal structures in exquisite detail. Highly accessible 3D interpretation promptly permitted precise measurements of repair-relevant anatomic parameters, including geometrically complex curves of the aortic root wall and dynamic changes in the aortic valves. Measurement accuracy examined against a known prosthesis showed within 1 mm of error (less than 0.5%). ConclusionsThis technology may promote understanding of aortic root form and function, and facilitate valve-sparing surgery, and seems valuable for 3D exploration and measurement of cardiac anatomy in vivo.

Overcurrent-driven LEDs for consistent image colour and brightness in agricultural machine vision applications

Machine vision systems are being utilized extensively in agriculture applications. Daytime imaging in outdoor field conditions presents challenges such as variable lighting and colour inconsistencies due to sunlight. Motion blur can occur due to vehicle movement and vibrations from ground terrain. A camera system with active lighting can be a solution to overcome these challenges. In this study, the usage of over-current driven LEDs to produce a powerful flash was investigated as a viable light source for daytime imaging. The current drawn by an LED was increased by a factor of six times its normal rating resulting in increased illuminance. A circuit was designed for storing and releasing energy to the LEDs for a strobe-like effect and a controller was used for synchronizing the strobe with a camera to acquire images. The system was deployed in an apple orchard on three days in summer of 2020. Images were taken throughout the day in both sunny and cloudy conditions of different canopy structures. There was substantial improvement in image brightness and colour consistency by using the LED flashes. Images captured by the prototype system during an 11-hour period showed an average decrease of 85% in standard deviation for the Hue-Saturation-Value (HSV) channels compared to that of the auto-exposure setting. Additionally, the prototype system was able to fix motion blur in images averaging 7 mm in error for a stereo vision application with the camera moving at 7 km/hr. These results show that the designed LED flash system can reduce the undesirable effects of lighting variability and motion blur in images stemming from outdoor field conditions.

Registration Techniques for Clinical Applications of Three-Dimensional Augmented Reality Devices.

Many clinical procedures would benefit from direct and intuitive real-time visualization of anatomy, surgical plans, or other information crucial to the procedure. Three-dimensional augmented reality (3D-AR) is an emerging technology that has the potential to assist physicians with spatial reasoning during clinical interventions. The most intriguing applications of 3D-AR involve visualizations of anatomy or surgical plans that appear directly on the patient. However, commercially available 3D-AR devices have spatial localization errors that are too large for many clinical procedures. For this reason, a variety of approaches for improving 3D-AR registration accuracy have been explored. The focus of this review is on the methods, accuracy, and clinical applications of registering 3D-AR devices with the clinical environment. The works cited represent a variety of approaches for registering holograms to patients, including manual registration, computer vision-based registration, and registrations that incorporate external tracking systems. Evaluations of user accuracy when performing clinically relevant tasks suggest that accuracies of approximately 2 mm are feasible. 3D-AR device limitations due to the vergence-accommodation conflict or other factors attributable to the headset hardware add on the order of 1.5 mm of error compared to conventional guidance. Continued improvements to 3D-AR hardware will decrease these sources of error.

Accuracy of cortical bone trajectory screw placement in midline lumbar fusion (MIDLF) with intraoperative cone beam navigation.

Cortical bone trajectory (CBT) screws have been recently described as a method of lumbosacral fixation. These screws are typically inserted under fluoroscopic guidance with a medial-to-lateral trajectory in the axial plane and a caudal-to-cephalad trajectory in the sagittal plane. In an effort to reduce surgeon radiation exposure and improve accuracy, CBT screws may be inserted under navigation with intraoperative cone beam computed tomography (CT). However, the accuracy of CBT screw placement under intraoperative navigation has yet to be assessed in the literature. The purpose of the study was to evaluate the accuracy of CBT screw placement using intraoperative cone beam CT navigation. One hundred and thirty-four consecutive patients who underwent CBT fixation with 618 screws under intraoperative navigation were analyzed from May 2016 through May 2018. Screws were placed by one of three senior spine surgeons using the Medtronic O-Arm Stealth Navigation. Screw position and accuracy were assessed on intraoperative and postoperative CT scans using 2D and 3D reconstructions with VitreaCore software. The majority of surgeries were primary cases (73.1%). The mean age at the time of surgery was 61.5±10.0 years and the majority of patients were female (61.2%). Most patients underwent surgery for a diagnosis of degenerative spondylolisthesis (47.8%) followed by mechanical collapse with foraminal stenosis (22.4%). Ten violations of the vertebral cortex were noted with an average breach distance of 1.0±0.7 mm. Three breaches were lateral (0.5%) and seven were medial (1.1%). The overall navigated screw accuracy rate was 98.3%. The accuracy to within 1 mm of error was 99.2%. There were no intra-operative neurologic, vascular, or visceral complications related to the placement of the CBT screws. CBT screw fixation under an intraoperative cone beam CT navigated insertion technique is safe and reliable. Despite five breaches greater than 1mm, there were no complications related to the placement of the CBT screws in this series.

Global gravity models and the Ghanaian Vertical Datum: challenges of a proper definition

This paper analyzes errors in satellite gravity and GPS/trigonometric benchmarks (BMs) in relation to defining the Ghanaian Vertical Datum (GhVD). Results indicate that synthesized gravity introduce approximately 5 mm of error to corrected heights. However, large errors in BMs render them unsuitable for applications, including properly defining the GhVD. Overall, normal-orthometric corrections were of the order of a few millimetres, with comparatively larger Helmert orthometric and normal corrections. Accordingly, the most suitable heights for the GhVD are the normal-orthometric heights, with the geopotential of the Helmert orthometric heights, m s, suggested as the potential of the GhVD.

Self-weighted NOSER-prior electrical impedance tomography using internal electrodes in cardiac radiofrequency ablation

Objective: Radiofrequency (RF) cardiac ablation is a commonly used method for treating cardiac arrhythmias in which the information of the dynamic lesion heating is critical to cardiologists but is currently lacking. Electrical impedance tomography (EIT) is a temporal modality of imaging the changes in the electrical properties within a measured object and hence might be able to track the electrical variation due to temperature changes within the myocardium. Within this paper, (1) a time-efficient algorithm with self-weighted NOSER-prior and (2) a measurement filtering process for optimizing the number of measurement were proposed for monitoring the lesion size during the cardiac RF ablation, taking advantage of internal catheter-based electrodes and the prior information of anatomical structure and the catheter location, which are usually available during the ablation course. Approach: A tank model with a circular myocardium of 12 mm in thickness, 16 external electrodes on the boundary and three internal catheter-based electrodes positioned inside the endocardium were made. The ablations were simulated using Pennes’ bioheat transfer equation and the simulated temperature gradients were then transferred to EIT measurements. The algorithm used one reference ablation for its optimization and then was tested with numerous 90 s ablations containing three disturbances: the catheter location mapping, the wide range of varied myocardium conductivity and the blood’s cooling convection, and the Gaussian noises with 10–40 µV in standard deviation. Main results: The results showed that, with the optimized number of 55 measurements, the algorithm still performed well when dealing with all three disturbances plus the random noises up 25 µV. Specifically, the lesion depth and width were measured within 1.6 mm and 3.2 mm in error respectively in at least 80% out of 100 simulated ablations. Significance: The algorithm has successfully measured the lesion size with good accuracy and tolerances of noise and other system perturbations. More tests in vitro and in vivo are required in the future to confirm the algorithm’s feasibility.

Effects of gleno-humeral joint centre mislocation on gleno-humeral kinematics and kinetics

The gleno-humeral (GH) rotation centre is typically estimated using predictive or functional methods, however these methods may lead to location errors. This study aimed at determining a location error threshold above which statistically significant changes in the values of kinematic and kinetic GH parameters occur. The secondary aims were to quantify the effects of the direction of mislocation (X, Y or Z axis) of the GH rotation centre on GH kinematic and kinetic parameters.Shoulder flexion and abduction movements of 11 healthy volunteers were recorded using a standard motion capture system (Vicon, Oxford Metrics Ltd, Oxford, UK), then GH kinematic and kinetic parameters were computed. The true position of the GH rotation centre was determined using a low dose x-ray scanner (EOS™ imaging, France) and this position was transferred to the motion data. GH angles and moments were re-computed for each position of the GH rotation centre after errors of up to ± 20 mm were added in increments of ± 5 mm to each axis. The three-dimensional error range was 5 mm to 34.65 mm.GH joint angle and moment values were significantly altered from 10 mm of three-dimensional error, and from 5 mm of error on individual axes. However, errors on the longitudinal and antero-posterior axes only caused very small alterations of GH joint angle and moment values respectively. Future research should develop methods of GH rotation centre estimation that produce three-dimensional location errors of less than 10 mm to reduce error propagation on GH kinematics and kinetics.

Multi-slit prompt-gamma camera for locating of distal dose falloff in proton therapy

Abstract In this research, a multi-slit prompt-gamma camera was developed to locate the distal dose falloff of the proton beam spots in spot scanning proton therapy. To see the performance of the developed camera, therapeutic proton beams were delivered to a solid plate phantom and then the prompt gammas from the phantom were measured using the camera. Our results show that the camera locates the 90% distal dose falloff (= d90%), within about 2–3 mm of error for the spots which are composed 3.8 × 108 protons or more. The measured location of d90% is not very sensitive to the irradiation depth of the proton beam (i.e., the depth of proton beam from the phantom surface toward which the camera is located). Considering the number of protons per spot for the most distal spots in typical treatment cases (i.e., 2 Gy dose divided in 2 fields), the camera can locate d90% only for a fraction of the spots depending on the treatment cases. However, the information of those spots is still valuable in that, in the multi-slit prompt-gamma camera, the distal dose falloff of the spots is located solely based on prompt gamma measurement, i.e., not referring to Monte Carlo simulation.

A comparative study of in-field motion capture approaches for body kinematics measurement in construction

SummaryDue to physically demanding tasks in construction, workers are exposed to significant safety and health risks. Measuring and evaluating body kinematics while performing tasks helps to identify the fundamental causes of excessive physical demands, enabling practitioners to implement appropriate interventions to reduce them. Recently, non-invasive or minimally invasive motion capture approaches such as vision-based motion capture systems and angular measurement sensors have emerged, which can be used for in-field kinematics measurements, minimally interfering with on-going work. Given that these approaches have pros and cons for kinematic measurement due to adopted sensors and algorithms, an in-depth understanding of the performance of each approach will support better decisions for their adoption in construction. With this background, the authors evaluate the performance of vision-based (RGB-D sensor-, stereovision camera-, and multiple camera-based) and an angular measurement sensor-based (i.e., an optical encoder) approach to measure body angles through experimental testing. Specifically, measured body angles from these approaches were compared with the ones obtained from a marker-based motion capture system that has less than 0.1 mm of errors. The results showed that vision-based approaches have about 5–10 degrees of error in body angles, while an angular measurement sensor-based approach measured body angles with about 3 degrees of error during diverse tasks. The results indicate that, in general, these approaches can be applicable for diverse ergonomic methods to identify potential safety and health risks, such as rough postural assessment, time and motion study or trajectory analysis where some errors in motion data would not significantly sacrifice their reliability. Combined with relatively accurate angular measurement sensors, vision-based motion capture approaches also have great potential to enable us to perform in-depth physical demand analysis such as biomechanical analysis that requires full-body motion data, even though further improvement of accuracy is necessary. Additionally, understanding of body kinematics of workers would enable ergonomic mechanical design for automated machines and assistive robots that helps to reduce physical demands while supporting workers' capabilities.

TH‐CD‐207B‐05: Measurement of CT Bow‐Tie Profiles Using a Linear Array Detector

Purpose:To accurately measure CT bow‐tie profiles from various manufacturers and to provide non‐proprietary information for CT system modeling.Methods:A GOS‐based linear detector (0.8 mm per pixel and 51.2 cm in length) with a fast data sampling speed (0.24 ms/sample) was used to measure the relative profiles of bow‐tie filters from a collection of eight CT scanners by three different vendors, GE (LS Xtra, LS VCT, Discovery HD750), Siemens (Sensation 64, Edge, Flash, Force), and Philips (iBrilliance 256). The linear detector was first calibrated for its energy response within typical CT beam quality ranges and compared with an ion chamber and analytical modeling (SPECTRA and TASMIP). A geometrical calibration process was developed to determine key parameters including the distance from the focal spot to the linear detector, the angular increment of the gantry at each data sampling, the location of the central x‐ray on the linear detector, and the angular response of the detector pixel. Measurements were performed under axial‐scan modes for most representative bow‐tie filters and kV selections from each scanner. Bow‐tie profiles were determined by re‐binning the measured rotational data with an angular accuracy of 0.1 degree using the calibrated geometrical parameters.Results:The linear detector demonstrated an energy response as a solid state detector, which is close to the CT imaging detector. The geometrical calibration was proven to be sufficiently accurate (&lt; 1mm in error for distances &gt;550 mm) and the bow‐tie profiles measured from rotational mode matched closely to those from the gantry‐stationary mode. Accurate profiles were determined for a total of 21 bow‐tie filters and 83 filter/kV combinations from the abovementioned scanner models.Conclusion:A new improved approach of CT bow‐tie measurement was proposed and accurate bow‐tie profiles were provided for a broad list of CT scanner models.

Range precision in forestry with Reflectorless Total Station

The Reflectorless Total Station, a convenient and efficient instrument for distance measurement used more in construction surveying than in forestry, was employed to determine the influence of different factors, such as trees, walls, distance, and angle of incidence, on precision distance measurements in forestry and to determine its feasibility for use with forest surveys, a Reflectorless Total Station （SOKKIA SET1X Total Station） with trees and walls as survey targets was tested. Experimental results on precision of distance measurements showed that （1） the material quality of a wall had little effect, its error is about 0.5 mm; whereas, （2） different tree species has varying degrees of bark roughness, it had the most influence to precision distance. For example, maximum error reached 2.769 mm with a measuring distance of 20 m. （3） Surface color of the target object revealed that the darker the color the greater the influence with 1 mm of error for a 20 m distance. （4） The stability of reflected signals had an error proportional to the distance with close to 5 mm measurement error for 100 m. （5） When the angle of incidence was over 20, at 20 m the error was close to 2 mm. （6） for target trees with rough bark, randomly selected target points should be obtained to improve the precision of the distance measurement.［Ch, 2 fig. 6 tab. 17 ref.］

Effects of glenohumeral joint centre mislocation on shoulder kinematics and kinetics

The gleno-humeral (GH) rotation centre is typically estimated using predictive or functional methods, however these methods may lead to location errors. This study aimed at determining a location error threshold above which statistically significant changes in the values of kinematic and kinetic GH parameters occur. The secondary aims were to quantify the effects of the direction of mislocation (X, Y or Z axis) of the GH rotation centre on GH kinematic and kinetic parameters. Shoulder flexion and abduction movements of 11 healthy volunteers were recorded using a standard motion capture system (Vicon, Oxford Metrics Ltd, Oxford, UK), then GH kinematic and kinetic parameters were computed. The true position of the GH rotation centre was determined using a low dose x-ray scanner (EOS™ imaging, France) and this position was transferred to the motion data. GH angles and moments were re-computed for each position of the GH rotation centre after errors of up to ± 20 mm were added in increments of ± 5 mm to each axis. The three-dimensional error range was 5 mm to 34.65 mm. GH joint angle and moment values were significantly altered from 10 mm of three-dimensional error, and from 5 mm of error on individual axes. However, errors on the longitudinal and antero-posterior axes only caused very small alterations of GH joint angle and moment values respectively. Future research should develop methods of GH rotation centre estimation that produce three-dimensional location errors of less than 10 mm to reduce error propagation on GH kinematics and kinetics.

Gamma electron vertex imaging and application to beam range verification in proton therapy

This paper describes a new gamma-ray imaging method, "gamma electron vertex imaging (GEVI)," which can be used for precise beam range verification in proton therapy. In GEVI imaging, the high-energy gammas from a source or nuclear interactions are first converted, by Compton scattering, to electrons, which subsequently are traced by hodoscopes to determine the location of the gamma source or the vertices of the nuclear interactions. The performance of GEVI imaging for use in-beam range verification was evaluated by Monte Carlo simulations employing geant4 equipped with the QGSP_BIC_HP physics package. Our simulation results show that GEVI imaging can determine the proton beam range very accurately, within 2-3 mm of error, even without any sophisticated analysis. The results were obtained under simplified conditions of monoenergetic pencil beams stopped in a homogeneous phantom and on the basis of the obtained results it is expected to achieve submillimeter accuracy in proton beam range measurement. If future experimental work confirms the simulated results presented in this paper, the use of GEVI imaging is expected to have a great potential in increasing the accuracy of proton beam range verification in a patient, resulting in significant improvement of treatment effectiveness by enabling tight conformation of radiation dose to the tumor volume and patient safety.

An Accuracy Assessment of Forensic Computerized Facial Reconstruction Employing Cone‐Beam Computed Tomography from Live Subjects

The utilization of 3D computerized systems has allowed more effective procedures for forensic facial reconstruction. Three 3D computerized facial reconstructions were produced using skull models from live adult Korean subjects to assess facial morphology prediction accuracy. The 3D skeletal and facial data were recorded from the subjects in an upright position using a cone-beam CT scanner. Shell-to-shell deviation maps were created using 3D surface comparison software, and the deviation errors between the reconstructed and target faces were measured. Results showed that 54%, 65%, and 77% of the three facial reconstruction surfaces had <2.5 mm of error when compared to the relevant target face. The average error for each reconstruction was -0.46 mm (SD = 2.81) for A, -0.31 mm (SD = 2.40) for B, and -0.49 mm (SD = 2.16) for C. The facial features of the reconstructions demonstrated good levels of accuracy compared to the target faces.

Position error reduction in a mechanical tracking linkage for arthroscopic hip surgery

Position tracking is an important aspect of many computer-aided surgical techniques. Given the obstacles of current optical, electromagnetic, and mechanical systems for medical applications, this work investigates error reduction in a new mechanical tracking system developed for arthroscopic hip surgery. This new tracking linkage addresses the current contradictory requirements of a thin, small linkage for ease of surgical use and a large, bulky linkage for increased accuracy by using (1) kinematic redundancy and (2) data averaging and curve fitting. To reduce the position error in the proposed mechanical tracking linkage, four numerical techniques were applied to data from the linkage. Two averaging techniques and two curve fitting techniques were investigated. After implementing each numerical technique, error testing was performed to quantify improvement in performance. While the simple average and moving average techniques lowered the error by over 30%, these two methods were undesirable for the overall system performance. The lowest error was measured by the linear curve prediction method. This technique measured 0.552 mm of error, roughly half of the error measured by the control case. The quadratic prediction method reduced the error by 35% and had the lowest standard deviation in the measurements. The linear prediction technique was able to significantly lower the error measured by a kinematically redundant mechanical tracking linkage. While further testing is still necessary, this data suggests that a thin, small mechanical tracking linkage could achieve a high level of accuracy to be an appropriate choice for a surgical tracking application.

진단용 CT-모의치료기 테이블의 효율적인 교정 방법

본 연구는 진단용 CT 장치를 이용한 CT-모의치료기의 테이블 및 레이저 정렬 시스템과 횡단면 영상의 중심간 정렬을 개선하기 위한 효율적인 방법을 제안하고자 하였다. 본원에서 제작한 팬텀을 이용하여 AAPM TG66에서 제시하는 일일 정도관리를 시행하고 기하학적 삼각함수를 이용하여 레이저 정렬 시스템을 교정하였으며 교정 전, 후를 비교함으로서 교정방법에 대한 효율성을 검토하였다. 교정 전 영상의 중심간 오차는 3.82mm, 테이블 종축은 <TEX>$0.436^{\circ}$</TEX> 틀어져 진행하였다. 기하학적 삼각함수를 이용한 레이저 정렬 시스템의 교정 후 0.7mm의 중심간 오차가 발생하여 <TEX>${\pm}2mm$</TEX>의 허용오차 범위를 만족하였다. 설치 가동 중인 진단용 CT 장치를 방사선치료 전용 CT-모의치료기로 활용하는 경우 기하학적 정확도를 만족시키기 위한 테이블 교정은 기술적인 한계 뿐 만 아니라 시간 및 경제적 손실에 비하여 매우 비효율적이다. 그러나 레이저 정렬 시스템을 이용한 교정 방법은 경제적이고 비교적 간단하면서도 만족스러운 기하학적 정확도를 얻을 수 있어 임상에서 적용할 수 있는 효율적인 방법이라 사료된다. This study suggested that the table of CT-simulator and the laser alignment system using diagnostic CT scanner have an efficient method for improvement in alignment between the planned target center of traverse image with CT scanner. It was conducted on the daily QA when presented in the AAPM TG66 with correcting the laser alignment system using geometric trigonometric functions and investigated the effectiveness of correction methods as compared with those before and after correction. Before correction error was 3.82mm between the planned target center of image, the table longitudinal axis was twisted with 0.436o. The laser alignment system using geometric trigonometric functions in after correction was satisfied with tolerance limits of <TEX>${\pm}2mm$</TEX> when occurred about 0.7mm in errors between the planned target center. The table correction to satisfy the geometric accuracy is very inefficient over against the time and economic loss as well as technical limits in the case of application as only radiation therapy associated with CT-simulator with diagnostic CT scanner in use. But, the method which corrects the laser alignment system is economic and relatively simple with possibility of getting well geometric accuracy and we suppose that it is efficient method for applying in the clinic.