Average 3D Research Articles

3D magnetic seed localization for augmented reality in surgery

PurposeFor tumor resection, surgeons need to localize the tumor. For this purpose, a magnetic seed can be inserted into the tumor by a radiologist and, during surgery, a magnetic detection probe informs the distance to the seed for localization. In this case, the surgeon still needs to mentally reconstruct the position of the tumor from the probe’s information. The purpose of this study is to develop and assess a method for 3D localization and visualization of the seed, facilitating the localization of the tumor.MethodsWe propose a method for 3D localization of the magnetic seed by extending the magnetic detection probe with a tracking-based localization. We attach a position sensor (QR-code or optical marker) to the probe in order to track its 3D pose (respectively, using a head-mounted display with a camera or optical tracker). Following an acquisition protocol, the 3D probe tip and seed position are subsequently obtained by solving a system of equations based on the distances and the 3D probe poses.ResultsThe method was evaluated with an optical tracking system. An experimental setup using QR-code tracking (resp. using an optical marker) achieves an average of 1.6 mm (resp. 0.8 mm) 3D distance between the localized seed and the ground truth. Using a breast phantom setup, the average 3D distance is 4.7 mm with a QR-code and 2.1 mm with an optical marker.ConclusionTracking the magnetic detection probe allows 3D localization of a magnetic seed, which opens doors for augmented reality target visualization during surgery. Such an approach should enhance the perception of the localized region of interest during the intervention, especially for breast tumor resection where magnetic seeds can already be used in the protocol.

KINEMATICS OF LOWER LIMBS DURING SQUATTING FOR CHINESE MALE AND FEMALE YOUTHS

This research aimed to measure lower extremity kinematics for male and female youths during daily activities and to identify gender differences from kinematics of lower limbs. A total of 87 healthy participants, comprising 43 Chinese male youths and 44 female youths, were recruited from Anhui Polytechnic University to participate in this research. All participants were instructed to perform squatting activities on a soft mat starting from an upright position. Every participant completed six squatting exercises, and motion capture technology was used to gather 3D kinematic data. SPSS software was used for statistical analysis. The average 3D angles of the hip, knee, and ankle joints of male and female youths were calculated, and then the independent t-test was used for statistical significance. Data analysis showed no significant gender differences in the sagittal movements of the knee and ankle joints for Chinese male and female youths. The mean hip joint angle during squatting was [Formula: see text] for male youths and [Formula: see text] for female youths. The knee joint angle was [Formula: see text] for male youths and [Formula: see text] for female youths. With regard to ankle mobility, the hip and ankle ranges of motion were [Formula: see text] and [Formula: see text] for male youths and [Formula: see text] and [Formula: see text] for female youths. Both sexes showed significant gender differences in the nonsagittal plane. The range of motion (ROM) observed during deep squatting exceeds the ROM after arthroplasty for Chinese male and female youths. These findings contribute to a comprehensive understanding of deep squatting biomechanics for the Chinese population and provide a basis for mitigating hyperflexion exercises and fabricating appropriate joint injury prostheses. By understanding the specific movement patterns of Chinese male and female youths, healthcare professionals can develop individualized interventions and rehabilitation programs to improve functional outcomes, prevent joint injuries, and improve the overall quality of life. The research found significant gender differences for sagittal hip and anterior ankle movements of male youths during squatting. These findings shed light on the kinematics of lower limbs. They have the potential to influence future research and medical practice to improve joint health and functional mobility for Chinese male and female youths.

3D printed pyrography: Using wood filament and dynamic control of nozzle temperature for embedding shades of color in objects

Colors enhance the esthetic and functional aspects of three-dimensional (3D) printed objects via material extrusion (MEX). However, existing 3D printing techniques require additional materials and hardware that are either challenging to calibrate or too costly for average 3D printing users. This paper presents a fabrication technique we call 3D printed pyrography, which enables printing multiple shades of color and gradients using a wood filament and a single-nozzle extruder. We investigate the effects of printing temperature and speed on the color properties of wood filament (ColorFabb). Using Euclidean distance in CIELAB color space, we employed perceptual metrics to quantify color differences between samples with different print temperatures (minimum: 195°C, maximum: 300°C, and 5°C increment). As a result, we identified all samples had perceivable discrete colors (ΔE ≥ 1), and, by applying a more conservative threshold, we can refine the count to sixteen distinct colors (ΔE ≥ 2.3). This approach underscores the sensitivity of color perception to printing parameters and highlights the utility of ΔE in CIELAB parameters in discerning color differences in 3D printed objects. Furthermore, we encapsulate this information in a custom software interface. This tool allows users to specify shades or map photographic images directly onto 3D surfaces, and generates the G-code that modulates the nozzle temperature and achieves the desired shading. We demonstrate 3D printed pyrography through 11 applications, such as enhancing visual esthetics, offering visual guidance, and embedding markers to merge digital information with physical objects.

Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results.

Accurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In this study, we explore the application of a deep learning algorithm, YOLOv7, for detecting kidney tumors on contrast-enhanced MRI. We assessed the performance of YOLOv7 tumor detection on excretory phase MRIs in a large institutional cohort of patients with RCC. Tumors were segmented on MRI using ITK-SNAP and converted to bounding boxes. The cohort was randomly divided into ten benchmarks for training and testing the YOLOv7 algorithm. The model was evaluated using both 2-dimensional and a novel in-house developed 2.5-dimensional approach. Performance measures included F1, Positive Predictive Value (PPV), Sensitivity, F1 curve, PPV-Sensitivity curve, Intersection over Union (IoU), and mean average PPV (mAP). A total of 326 patients with 1034 tumors with 7 different pathologies were analyzed across ten benchmarks. The average 2D evaluation results were as follows: Positive Predictive Value (PPV) of 0.69 ± 0.05, sensitivity of 0.39 ± 0.02, and F1 score of 0.43 ± 0.03. For the 2.5D evaluation, the average results included a PPV of 0.72 ± 0.06, sensitivity of 0.61 ± 0.06, and F1 score of 0.66 ± 0.04. The best model performance demonstrated a 2.5D PPV of 0.75, sensitivity of 0.69, and F1 score of 0.72. Using computer vision for tumor identification is a cutting-edge and rapidly expanding subject. In this work, we showed that YOLOv7 can be utilized in the detection of kidney cancers.

Implementation of GAGAN augmentation on smart mobile devices and development of a cooperative positioning architecture

Abstract This study presents an Android-based cooperative positioning (CP) architecture to improve the GNSS positioning performance on mobile devices. SBAS (Satellite Based Augmentation System) augmentation increases positioning accuracies significantly by sharing corrections between SBAS-enabled and non-capable devices via wireless connection or using a central server. The Indian GAGAN (GPS Aided GEO Augmented Navigation) is employed and assessed in the experiments. If GAGAN corrections are applied, all three chosen mobile devices showed a positioning accuracy improvement of around 95 %. The average 2D RSME was reduced from 75.23 to 1.35 m for the single-frequency GNSS smartphone Xiaomi Redmi Note 8 and from 33.25 to 1.62 m for the dual-frequency Google Pixel 4. As expected, the third GIS mapping device, Stonex S70 tablet, showed the highest performance, achieving sub-meter positioning accuracies. Thus, the experiment has proven the suitability of GAGAN augmentation for mobile devices, providing positive insight for further development of the CP architecture.

Assessing iPhone LiDAR & Recon-3D for determining area of origin in bloodstain pattern analysis.

Bloodstain pattern analysis (BPA) has proven to be a useful tool in forensic and criminal investigations for quite some time. Traditionally, documenting a crime scene for a bloodletting event was completed using manual techniques, physical strings, and a tape measure. In more recent years, laser scanners and 3D software programs have become a preferred method to capture accurate data that improves the validity and reliability of BPA. The initial cost of laser scanning equipment is relatively high, rendering these systems inaccessible to some police and smaller agencies. Recon-3D is a newly developed iPhone application that utilizes the iPhone LiDAR sensor in combination with video data to create 3D point clouds of crime scenes. To assess the viability of Recon-3D for area of origin analysis, two tests were performed. One was a series of bloodstain impacts which were analyzed in FARO Zone 3D software, while the second was a series of 6 repeated Recon-3D scans of two 90-degree walls which was then compared to the FARO Focus S350 scanner using CloudCompare software. A total of eight impact patterns were made at three different distances from a wall. The area of origin was measured and compared to the known location of the blood source. The average total 3D error for the area of origin set at 25, 50, and 100 cm from two perpendicular walls was found to be 6.04, 15.16, and 36.59 cm, respectively. These results are similar to past studies where programs such as HemoSpat have been used. The results of the point cloud comparison show that on average, 95% of the points from Recon-3D fall below a threshold of 3.6 mm when compared to a FARO Focus S350 laser scanner. Thus, the results of this test suggest that Recon-3D is an accurate and affordable scanning application for bloodstain patterns at crime scenes and the data provide acceptable results for area of origin analysis in BPA programs which accept laser scanner data.

Correcting Projection Effects in CMEs Using GCS‐Based Large Statistics of Multi‐Viewpoint Observations

AbstractThis study addresses the limitations of single‐viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the Graduated Cylindrical Shell (GCS) model. The data set combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is ∼1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km s−1. AR and AP speeds are higher, at 723 and 813 km s−1, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of ∼2 km s−1 deg−1, which increases to 5 km s−1 deg−1 when the GCS‐fitted ‘true’ parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km s−1 deg−1, while AP CMEs show a gradient of 4 km s−1 deg−1. PE CMEs, however, lack a significant speed‐width relationship. We show that fitting multi‐viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.

Evaluation of three-dimensional reconstructed palatal morphology in skeletal class III subjects with different vertical patterns using cone beam computed tomography

BackgroundThis study aims to evaluate the difference of three-dimensional (3D) reconstructed palatal morphology between subjects with skeletal Class III and skeletal Class I in different vertical patterns using cone beam computed tomography (CBCT).MethodsIn this study, 89 subjects with skeletal Class III (49 females, 40 males; 25.45 ± 3.81 years) and 85 subjects with skeletal Class I (45 females, 40 males; 23.95 ± 4.45 years) were collected retrospectively and divided into hyperdivergent, normodivergent and hypodivergent groups. Dolphin software was used to reorient the CBCT images of these subjects. After segmenting 3D object of maxilla from the 3D skull by ProPlan software, Geomagic Studio was used to reconstruct 3D palatal morphology and establish an average 3D palatal morphology for each group. The differences of 3D palatal morphology between different groups were compared by deviation patterns on 3D colored map analysis.Results3D colored map analysis showed the posterior part of male’s palate was higher and wider than that of female’s palate in skeletal Class III subjects. In skeletal Class III subjects, males with hyperdivergent pattern had a higher and narrower palate compared with hypodivergent subjects, while females with hyperdivergent had a higher but not obviously narrower palate compared with hypodivergent subjects. In the similar vertical patterns, skeletal Class III subjects had a flatter but not narrower palate compared with skeletal Class I subjects, along with a smaller palate volume.ConclusionsThis method allows more intuitive between-group comparisons of the differences of 3D palatal morphology. In skeletal Class III subjects, as the vertical dimension increased, the palate tends to be higher and narrower. Therefore, the influence of vertical patterns on the palatal morphology should be fully considered in the orthodontic and orthognathic treatment of skeletal Class III subjects.

Investigation of Roughness, Morphology, and Wettability Characteristics of Biopolymer Composite Coating on SS 316L for Biomedical Applications.

This project aims to create a 316L stainless steel coated with a biocomposite based on chitosan for use in the biomedical industry. To completely coat the material, the dip-coating technique was used to apply plain chitosan, chitosan nanosilver, chitosan biotin, and chitosan-nanosilver-biotin in that order. This coating's surface morphology was investigated with field emission scanning electron microscopy (FESEM). Surface roughness, average size distribution, and 2D and 3D surface tomography were all investigated using scanning probe microscopy and atomic force microscopy (SPM and AFM). The Fourier transform infrared (FTIR) spectroscopy technique was used to quantify changes in functional groups. To evaluate the coated samples' wettability, contact angle measurements were also performed. The chitosan (CS) + nanosilver, CS + biotin, and CS + biotin + nanosilver-coated 316L stainless steel showed roughness values of about 8.68, 4.21, and 3.3 nm, respectively, compared with the neat chitosan coating, which exhibits 12 nm roughness, indicating a strong effect of biotin and nanosilver on surface topography whereas the coating layers were homogenous, measuring around 33 nm in thickness. For CS + nanosilver and CS + biotin, the average size of agglomerates was approximately 444 nm and 355 nm, respectively. The coatings showed adequate wettability for biomedical applications, were homogeneous, and had no cracks. Their contact angles were around 51-75 degrees. All of these results point to the composite coating's intriguing potential for use in biological applications.

Application of magnetic resonance imaging with intraoperative color Doppler ultrasound in the treatment of patients with polyacrylamide hydrogel injected for breast augmentation: a retrospective study of 204 cases for 12 years.

Polyacrylamide hydrogel (PAHG), which had been used widely for breast augmentation, has been banned for more than 15 years. Patients who had been injected PAHG for breast augmentation need evacuation surgery to remove as much as possible. To provide a series of diagnosis and treatment process MRI and intraoperative color Doppler ultrasound are combined for maximal removal of PAHG. The patients who received evacuation surgery in Peking University Third Hospital from 2010 to 2022 after PAHG injection for breast augmentation were included in this research. MR scanning was performed preoperatively and postoperatively in some of these patients and color Doppler ultrasound was applied to help evacuate PAHG intraoperatively. The mean clearance rate of PAHG was calculated according to the MRI outcomes. Two hundred and 4 patients had received evacuation surgery after PAHG injection for breast augmentation with an average age of 42.8 years and an average body mass index of 21.2 kg/m2. The average PAHG retention time was 13.5 years. Among them, 52 patients underwent pre- and postoperative MRI scanning. The mean three-dimensional (3D) volume of PAHG was 684.8 mL (range, 350.0-1,123.9 mL), and the average residual 3D volume of PAHG was 53.7 mL (range, 12.4-98.3 mL). The mean clearance rate was 92.1%. MRI and intraoperative color Doppler ultrasound can provide effective and precise location information of PAHG for evacuation surgery, which is a reliable method to ensure the maximal removal of PAHG.

Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.

Purpose: Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (CNN) using a multichannel input method. Methods: A target conformal plan (TCP) was created based on the maximum planning target volume (PTV). Input data included TCP dose distribution, images, target structures, and organ-at-risk (OAR) information. The role of target conformal plan dose (TCPD) was assessed by comparing the TCPD-CNN (with dose information) and NonTCPD-CNN models (without dose information) using statistical analyses with the ranked Wilcoxon test (P < .05 considered significant). Results: The TCPD-CNN model showed no statistical differences in predicted target indices, except for PTV60, where differences in the D98% indicator were < 0.5%. For OARs, there were no significant differences in predicted results, except for some small-volume or closely located OARs. On comparing TCPD-CNN and NonTCPD-CNN models, TCPD-CNN's dose-volume histograms closely resembled clinical plans with higher similarity index. Mean dose differences for target structures (predicted TCPD-CNN and NonTCPD-CNN results) were within 3% of the maximum prescription dose for both models. TCPD-CNN and NonTCPD-CNN outcomes were 67.9% and 54.2%, respectively. 3D gamma pass rates of the target structures and the entire body were higher in TCPD-CNN than in the NonTCPD-CNN models (P < .05). Additional evaluation on previously unseen volumetric modulated arc therapy plans revealed that average 3D gamma pass rates of the target structures were larger than 90%. Conclusions: This study presents a novel framework for dose distribution prediction using deep learning and multichannel input, specifically incorporating TCPD information, enhancing prediction accuracy for IMRT in NPC treatment.

A multiscale approach to assess thermomechanical performance and force generation in nanorobotic microgels.

We present a multiscale approach to characterize the performance of photothermally powered, nanorobotic 3D microgels. Optically triggered nanoactuators, consisting of a gold nanorod core and thermoresponsive pNIPMAM shell, are used as building blocks to generate the nanorobotic 3D microgels. We use microfluidic encapsulation to physically embed the nanoactuators in an alginate network, to form the microgel droplets. The nanoactuators respond to near-infrared light owing to the synergistic effects of plasmonic and thermoresponsive components, and the nanorobotic 3D microgels generate compressive force under the same light stimulus. We use a multiscale approach to characterize this behavior for both the nanoactuators and the assembled microgels via dynamic light scattering and fluorescence microscopy, respectively. A thermoresponsive fluorescent molecule, Rhodamine B, is integrated into alginate chains to monitor the temperature of the microgels (22-59 °C) during actuation at laser intensities up to 6.4 μW μm-2. Our findings show that nanoactuators and the microgels exhibit reversible deformation above the lower critical solution temperature of the thermoresponsive polymer at 42 °C. 785 nm laser light triggers the generation of 2D radial strain in nanoactuators at a maximum of 44%, which translates to an average 2D radial strain of 2.1% in the nanorobotic microgels at 26.4 vol% nanoactuator loading. We then use a semi-experimental approach to quantify the photothermally generated forces in the microgels. Finite element modeling coupled with experimental measurements shows that nanorobotic microgels generate up to 8.5 nN of force over encapsulated single cells. Overall, our method provides a comprehensive approach to characterizing the mechanical performance of nanorobotic hydrogel networks.

Effect of a confidence-based weighted 3D point reconstruction for markerless motion capture with a reduced number of cameras

ABSTRACTMarkerless motion capture has been made available by the development of pose estimation algorithms that provide both an estimate of the location of body keypoints in two-dimensional images and its associated confidence. It seems relevant to use this additional information for three-dimensional (3D) point reconstruction. Yet, it has been little described, nor has its influence on 3D point reconstruction. Eight participants performed a manual material handling task, which was recorded by 10 video cameras. Each video was processed using OpenPose. Different 3D point reconstruction methods were compared: direct linear transform (DLT) and weighted DLT (wDLT), with 10 cameras and with a subset of 4 cameras. For each keypoint, confidence and position deviation from the 3D reconstructed point with 10 cameras projected in the image reference frame were assessed. Results suggest that using confidence information reduces both average and maximum 3D distance between 3D points reconstructed with 4 and 10 cameras.

Evolution of surface roughness of notched steel details under fatigue loading

A fatigue crack initiates on the surface of the steel members, which can be attributed to the extrusions and intrusions caused by cyclic loading. The surface roughness parameters, including the statistical surface roughness and maximum surface roughness parameters, can characterize the increase in extrusion and intrusion. Six notched specimens were loaded with cyclic loading, and the evolution of the surface roughness parameters was monitored during the test to explore the characteristics of the surface roughness during the fatigue loading procedure in the high-cycle fatigue regime and clarify the effects of the initial surface finish and load ratio on the surface roughness evolution. Based on the test results, it was found that the 3D average surface roughness Sa and 3D root-mean-square surface roughness Sq were preferable for detecting the onset of fatigue cracks compared with the 2D average surface roughness Ra and 2D root-mean-square surface roughness Rq. The 3D maximum valley depth, Sv, was an effective indicator of the fatigue crack initiation location, except for compression-dominant fatigue loading. The evolution patterns of the 3D average surface roughness, Sa, and 3D root-mean-square surface roughness Sq during fatigue loading can be classified into three phases: instant response, damage accumulation, and crack-induced response. In addition, surface polishing is recommended for evaluation using 2D surface roughness parameters. However, it is not mandatory for evaluations using 3D surface roughness parameters. The effects of typical load ratios (0.1, −1, and 10) on the evolution pattern of the 3D statistical surface roughness parameters, especially in the instant response phase, were also investigated.

The Creation of an Average 3D Model of the Human Cartilaginous Nasal Septum and Its Biomimetic Applications.

The cartilaginous nasal septum is integral to the overall structure of the nose. Developing our an-atomic understanding of the septum will improve the planning and techniques of septal surgeries. While the basic dimensions of the septum have previously been described, the average shape in the sagittal plane has yet to be established. Furthermore, determining the average shape allows for the creation of a mean three-dimensional (3D) septum model. To better understand the average septal shape, we dissected septums from 40 fresh human cadavers. Thickness was measured across pre-defined points on each specimen. Image processing in Photoshop was used to superimpose lateral photographs of the septums to determine the average shape. The average shape was then combined with thickness data to develop a 3D model. This model may be utilized in finite elemental analyses, creating theoretical results about septal properties that are more translatable to real-world clinical practice. Our 3D septum also has numerous applications for 3D printing. Realistic models can be created for educational or surgical planning purposes. In the future, our model could also serve as the basis for 3D-printed scaffolds to aid in tissue regeneration to reconstruct septal defects. The model can be viewed at the NIH 3D model repository (3DPX ID: 020598, Title: 3D Nasal Septum).

The Evaluation of Muller Weiss Diseased and Normal Feet on a Three-Dimensional Foot Model

Category: Hindfoot; Midfoot/Forefoot Introduction/Purpose: The deformities associated with Müller Weis Disease (MWD) have not been well understood which inevitably impacts clinical and surgical decision making. Despite most previous studies characterizing MWD as a paradoxical flatfoot deformity, ie, a flat arch and a varus heel, some studies have treated MWD as a flatfoot deformity by performing a medializing calcaneus osteotomy, and others as an arthritic disorder treated with hind foot arthrodesis but without correcting the deformity. This study used an automatic 3D segmentation program to create an average 3D foot model for both normal controls and a large group of MWD feet, to demonstrate the deformity pattern, and to provide surgeons with a foundation for detailed alignment evaluation and surgical planning. Methods: Weight bearing Scans of 55 health feet without deformities, trauma and surgical histories, and 69 MWD feet were included in this study. The Bonelogic program (Disior, Paragon 28,) was used to automatically segment the bones and 3D information of each foot in the same group was pooled to create an average foot model for both the controls and the MWD feet. Videos were created using all feet in both groups to demonstrate the deformity patterns ranging from normal feet transitioning to MWD feet. Since current axial and angular metrics for alignment evaluation using traditional 2D imaging cannot be extrapolated to 3D this study was kept as a descriptive paper, and no traditional metrics were analyzed and reported. Results: Compared to the average normal foot, the MWD foot model demonstrated the following features: narrowing on the lateral pole and dorsal side of the navicular, lateral rotation and slight dorsal lifting of the talar head and medial rotation of the navicular, a varus heel with more opening in the sinus tarsi, proximal shift of the calcaneal tuberosity, a flat medial arch with subsidence at the talonavicular joint, decreased adduction of the forefoot, medial translation of the cuboid at the calcaneocuboid articulation, and a shortened 1st metatarsal. All of the above changes were consistently demonstrated in video one (a comparison between the two foot models), and video two (a comparison of the peritalar joint alignment between the two groups). Conclusion: The foot models were built up with pixels, with each pixel carrying its own 3D information in space allowing exploration of real 3D alignment evaluation tools. The MWD foot model clearly demonstrated and validated the deformity patterns originally described by Maceira, and subsequently by other authors using both radiographs and WBCT scans. This model facilitates evaluation of alignment from the hindfoot to the forefoot, as well as advanced 3D analysis to assess the morphology of the bones and joints and can be the foundation for surgical planning and predication of outcomes.

Evaluation of Patient-Specific Quality Control (QC) for Markerless Dynamic Tumor Tracking (MDTT) Deliveries

To report on the patient-specific QC for MDTT for liver and lung tumors treated using the dome-of-liver/diaphragm as a surrogate for the target position and compare to the QC of conventional fiducial-based tracking. Vero4DRT is a linear accelerator that has a gimbal-mounted waveguide and collimation system allowing the radiation beam to perform dynamic tumor tracking based on a patient's respiratory motion. A correlation model is built between an external IR marker placed on the chest and an internal structure, which may be implanted fiducial surrogates or in the case of MDTT, an anatomic landmark. During treatment an orthogonal kV image pair is taken every second. The auto detected internal structure position versus the predicted position is recorded in treatment log files. Five IMRT tracking plans were delivered to two commercial motion phantoms with in-house additions for patient-specific tracking QC. For point dose measurements, a 0.6cc farmer chamber was placed inside the dynamic tracking phantom which contains fiducials for fiducial-based tracking delivery and an anatomic landmark for MDTT. For 2D dose distribution measurements, a radiographic film insert for the Quasar Respiratory Motion Phantom was constructed. The phantom contains both fiducials and has a liver-dome shape at one end to facilitate MDTT. Both motion platforms were interfaced with software that enabled patient-specific respiratory motion traces acquired during a 4DCT scan. Each plan was delivered three times on each phantom: 1) in static mode, 2) during fiducial-based tracking, and 3) during MDTT. Chamber measurements taken during static and tracked delivery were compared to the average chamber dose from the treatment planning software (TPS). Film distributions measured during tracked deliveries were compared to the static film distribution using gamma analysis with FILMQA PRO software. Finally, dynamic tracking treatment statistics, extracted from log files, were compared between fiducial and markerless tracking deliveries. All chamber measurements resulted in dose differences <2.5% compared with the TPS. Dose differences between fiducial-based and MDTT were 0.26% on average (range 0.03-0.62%). For film dose map analysis, gamma pass rates were >95% for all plans for all tracking methods. The average gamma pass rate for 3%/3mm was 99.4% (fiducial-based) vs 98.4% (markerless). For 2%/2mm, the average gamma pass rate was 96.4% (fiducial-based tracking) vs 95.6% (MDTT). Dynamic treatment statistics from logs files reported an average 3D absolute deviation from predicted position of 0.52mm (±0.24) for fiducial tracking and 1.19mm (±0.50) for MDTT. Both fiducial-based and MDTT plans meet passing criteria for patient-specific QC. 3D absolute deviation of detected versus predicted position are larger for MDTT compared to fiducial tracking, however no significant impact on dose delivery was measured.

Impact of anthropometry training and feasibility of 3D imaging on anthropometry data quality among children under five years in a postmortem setting.

The Child Health and Mortality Prevention Surveillance Network (CHAMPS) identifies causes of under-5 mortality in high mortality countries. To address challenges in postmortem nutritional assessment, we evaluated the impact of anthropometry training and the feasibility of 3D imaging on data quality within the CHAMPS Kenya site. Staff were trained using World Health Organization (WHO)-recommended manual anthropometry equipment and novel 3D imaging methods to collect postmortem measurements. Following training, 76 deceased children were measured in duplicate and were compared to measurements of 75 pre-training deceased children. Outcomes included measures of data quality (standard deviations of anthropometric indices and digit preference scores (DPS)), precision (absolute and relative technical errors of measurement, TEMs or rTEMs), and accuracy (Bland-Altman plots). WHO growth standards were used to produce anthropometric indices. Post-training surveys and in-depth interviews collected qualitative feedback on measurer experience with performing manual anthropometry and ease of using 3D imaging software. Manual anthropometry data quality improved after training, as indicated by DPS. Standard deviations of anthropometric indices exceeded limits for high data quality when using the WHO growth standards. Reliability of measurements post-training was high as indicated by rTEMs below 1.5%. 3D imaging was highly correlated with manual measurements; however, on average 3D scans overestimated length and head circumference by 1.61 cm and 2.27 cm, respectively. Site staff preferred manual anthropometry to 3D imaging, as the imaging technology required adequate lighting and additional considerations when performing the measurements. Manual anthropometry was feasible and reliable postmortem in the presence of rigor mortis. 3D imaging may be an accurate alternative to manual anthropometry, but technology adjustments are needed to ensure accuracy and usability.

A simulation study on spatial and time resolution for a cost-effective positron emission particle tracking system

This work is the second part of a simulation study investigating the processing of densely packed and moving granular assemblies by positron emission particle tracking (PEPT). Since medical positron emission tomography (PET) scanners commonly used for PEPT are very expensive, a PET-like detector system based on cost-effective organic plastic scintillator bars is being developed and tested for its capabilities. In this context, the spatial resolution of a resting positron source, a source moving on a freely designed model path, and a particle motion given by a discrete element method (DEM) simulation is studied using Monte Carlo simulations and the software toolkit Geant4. This not only extended the simulation and reconstruction to a moving source but also significantly improved the spatial resolution compared to previous work by adding oversampling and iteration to the reconstruction algorithm. Furthermore, in the case of a source following a trajectory developed from DEM simulations, a very good resolution of about 1 mm in all three directions and an average 3D deviation between simulated and reconstructed events of 2.3 mm could be determined. Thus, the resolution for realistic particle motion within the generic grate system (which is the test rig for further experimental studies) is well below the smallest particle size. The simulation of the dependence of the reconstruction accuracy on tracer particle location revealed a nearly constant efficiency within the entire detector system, which demonstrates that boundary effects can be neglected.

Underwater laser positioning of targets outside the field of view based on a binocular vision.

An underwater laser positioning scheme based on a binocular camera is introduced. In spite of the scattering, the underwater laser light path can be clearly captured by a camera within an appropriate range depending on the water turbidity. For an emitting laser with a fixed position, the three-dimensional information of the laser source can be calculated from the beam images captured by a binocular camera, even if the laser is out of the camera's field of view (FOV). This method can break through the FOV limitation of traditional camera positioning and perform a 3D spatial positioning for the target even outside the FOV of the camera. We simulate and analyze the scattering light imaging and find that the laser propagation direction can be recognized from the scattering image. The experimental results show that the proposed underwater positioning scheme achieves an average 3D positioning error of 5.53cm within a range of 5m when the underwater attenuation is 0.325m -1.