Search Results (128)

The quality of digital 3D models of fossils is important from the perspective of their further usage, either for scientific or didactical purposes. However, fidelity evaluation has rarely been attempted for digitized fossil objects. In the present research, a 3D triangulated model of the unique skull of Madygenerpeton pustulatum was built using an YXLON µCT device. The comparative analysis was performed using models obtained from seven optical surface-scanning systems. Methodology for accuracy assessment involved the determination of distances between the points in pairs of models, interchanging the reference and tested ones. Statistical significance testing using paired t-tests was performed. In particular, it was found that the YXLON µCT model was closest to the one obtained from AICON SmartScan, exhibiting an average distance of $\overline{{∆}_d}$ = −0.0183 mm with a standard deviation of σ{∆_d} = 0.0778 mm, which is close to the permissible error of 20 µm given in technical specifications for AICON scanners. It was demonstrated that the analysis maintained measurement validity even though the YXLON model consisted of 23.8 M polygons and the AICON model consisted of 13.9 M polygons. Comparison with other digital models demonstrated that the fidelity of the triangulated µCT model made it feasible for further research and dissemination purposes. Full article

Some laser scanners utilize stepper motor-driven optomechanical assemblies to position the laser beam precisely during triangulation. In laser scanners such as the presented Technical Vision System (TVS), to enhance motion resolution, gear transmissions are implemented between the motor and the optical assembly. However, due to the customized nature of the mechanical design, errors in manufacturing or insufficient mechanical characterization can introduce deviations in the computed 3D coordinates. In this work, we present a novel method for estimating the degrees-per-step ratio at the output of the laser positioner’s transmission mechanism using a stereovision system. Experimental results demonstrate the effectiveness of the proposed method, which reduces the need for manual metrological instruments and simplifies the calibration procedure through vision-assisted measurements. The method yielded estimated angular resolutions of approximately 0.06° and 0.07° per motor step in the horizontal and vertical axes, respectively, key parameters that define the minimal resolvable displacement of the projected beam in dynamic triangulation. Full article

Assessing the variation in the thermal conductivity of heterogeneous rock materials can be critical when upscaling models to simulate geothermal system operation, especially for petrothermal systems, where conduction dominates over convection. This study’s objective was to evaluate heterogeneity effects when assessing the thermal conductivity of geological materials, in this case, metamorphic rocks from Kuujjuaq (Canada), where the installation of a ground-coupled heat pump system is expected. Four core samples of gneissic rocks were analyzed in detail and compared to results obtained from a thermal response test. Thermal conductivity measurements in dry conditions were performed on the cylindrical surface of the samples with an optical thermal conductivity scanner. The 2D thermal conductivity spatial distribution was obtained by linear interpolation and used for numerical modeling to simulate steady-state conductive heat transfer along the sample vertical direction. Then, the effective thermal conductivity was computed according to Fourier’s law, using the simulated temperature to investigate the effect of scale variation with the heterogeneity. Results indicate the importance of distinguishing between the sample section’s effective thermal conductivity and local average thermal conductivity. Significant scale effects were identified with a variation ratio comprised between −10% and +16% when varying the length of the sample section. The representative elementary volume for the effective thermal conductivity was determined equivalent to half of the sample length. This volume gave a thermal conductivity that is equal to the harmonic mean of the laboratory-assessed values with a relative error <5%. A comparison between the in situ and laboratory-assessed thermal conductivity indicates that the thermal conductivity inferred from the thermal response test is adequate for sizing a geothermal system, assuming a range of variability equivalent to 1.5 times its standard deviation. Full article

Background: Accuracy of optical impressions—defined by the intraoral scanner (IOS)’s trueness and precision per International Organization for Standardization (ISO) standards—is influenced by both operator- and patient-related factors. Thus, this in vitro study aimed to (1) evaluate how scanning distance affects the accuracy of three different intraoral scanners (IOSs), and (2) identify the optimal scanning distance for each scanner. Methods: A maxillary arch model was obtained using polyvinyl siloxane impression material and poured with Type IV stone (Octa-rock royal^®, Kulzer, Germany). Using three different types of IOSs—the trios 3 shape (TRIOS ^® cart, 3Shape, Copenhagen, Denmark); the Helios 500 (Eighteeth ^®, Changzhou, China); and the Heron (3Disc ^®, Herndon, VA 20170, USA)—ten scans were performed with each of the IOSs with five predetermined distances: 0 mm, 2.5 mm, 5 mm, 7.5 mm, and 10 mm. Spacers of varying heights were designed using Meshmixer version 3.5 (Autodesk, Inc., Mill Valley, CA, USA) and three-dimensional printed with the Form 2 printer (Formlabs, Somerville, MA, USA). The scanned data was processed using Geomagic Control X (Version 16.0.2.16496, 3D Systems, Wilsonville, OR, USA). Statistical analyses were performed using R Statistical Software (version 4.2.2), with significance set at α = 0.05. Results: Scanning distance significantly influenced scan accuracy for all three scanners. The 3Disc scanner (3Disc, Herndon, VA, USA) demonstrated the highest accuracy at a 7.5 mm distance, while both the Helios 500 (Eighteeth, Changzhou, China) and Trios 3 (3Shape, Copenhagen, Denmark) scanners achieved their best accuracy at a 5 mm distance, as indicated by the lowest root mean square (RMS) values (p < 0.05). Conclusions: To conclude, each IOS has an optimal scanning distance for best accuracy. Trios 3 (3Shape, Copenhagen, Denmark) outperformed the others in both trueness and precision. Future studies should examine these effects under full-arch and clinical conditions. Full article

Background/Objectives: The introduction of composite attachments has greatly improved orthodontic aligner therapy, through better force delivery, more predictable movements, and enhanced retention. This in vitro study aims to present and investigate an innovative digital protocol for aligner attachment fabrication incorporating the latest 3D technology used in dentistry. Methods: A virtual attachment measuring 2.5 × 2 × 2 mm was designed using computer-aided design (CAD) software (Meshmixer, Autodesk Inc., San Francisco, CA, USA) and exported as an individual STL file. The attachments were fabricated using a digital light processing (DLP) 3D printer (model: Elegoo 4 DLP, Shenzhen, China) and a dental-grade biocompatible resin. A custom 3D-printed placement guide was used to ensure precise positioning of the attachments on the printed maxillary dental models. A flowable resin was applied to secure the attachments in place. Following attachment placement, the models were scanned using a laboratory desktop scanner (Optical 3D Smart Big, Open Technologies, Milano, Italy) and three intraoral scanners: iTero Element (Align Technology, Tempe, AZ, USA), Aoral 2, and Aoral 3 (Shining 3D, Hangzhou, China). Results: Upon comparison, the scans revealed that the iTero Element exhibited the highest precision, particularly in the attachment, with an RMSE of 0.022 mm and 95.04% of measurements falling within a ±100 µm tolerance. The Aoral 2 scanner showed greater variability, with the highest RMSE (0.041 mm) in the incisor area and wider deviation margins. Despite this, all scanners produced results within clinically acceptable limits. Conclusions: In the future, custom attachments made by 3D printing could be a valid alternative to the traditional composite attachments when it comes to improving aligner attachment production. While these preliminary findings support the potential applicability of such workflows, further in vivo research is necessary to confirm clinical usability. Full article

The dimensional accuracy of 3D-printed edentulous jaw models is critical for successful prosthetic treatment outcomes. This study investigated the accuracy of 3D-printed working models of a completely edentulous jaw through comparative analysis of digital images generated by three laboratory scanners. A reference plaster model of a mandibular edentulous arch was digitized and used to produce ten resin models via digital light processing (DLP) technology. Each model was scanned using three different laboratory scanners: AutoScan-DS-EX, AutoScan-DS-EX Pro(H), and Optical 3D Scanner Vinyl. Digital comparison was performed using specialized software, evaluating the root mean square (RMS) deviation and percentage of values within an acceptable deviation range ±0.05 mm. All printed models showed significant deviations from the reference model (p < 0.05), with RMS values ranging from 109.2–139.7 µm and acceptable deviation percentages ranging from 29.34 to 32.31%. The mean precision RMS value was 66.37 µm. The mean intraclass correlation coefficient of 0.544 indicated moderate precision. Optical 3D Scanner Vinyl demonstrated the highest consistency, while AutoScan-DS-EX Pro(H) showed maximum variability. No statistically significant differences were found between scanners (p = 0.075). While the investigated scanners demonstrated reliable performance and sufficient accuracy, the additive manufacturing process introduced clinically significant deviations, highlighting the importance of verification between printed models and their digital originals before proceeding with clinical stages. Clinical practice should prioritize scanning systems with advanced software algorithms over those with superior hardware specifications alone. Full article

Additive manufacturing, in combination with virtual surgery planning, leads to the predictability of complex surgical cases. To guarantee patient safety, three-dimensional (3D) print quality must be ensured and verified. The aim of this study is to compare the accuracy of an optical white-light desktop scanner (OWLDS) and a cone beam CT (CBCT) scanner to that of a multi-slice CT scanner (MSCT) for scanning and digitizing 3D anatomical models. Twenty-two removable parts of a CE-certified anatomical skull, used as a patient-specific surrogate in a clinical workflow, were each scanned by MSCT, CBCT, and OWLDS scanners. The accuracy of the scanning modalities was investigated through a part comparison analysis of the stereolithography (STL) files derived from the different scanning modalities. The high-resolution OWLDS STL files show the smallest overall surface match deviation, at 0.04 mm, compared to the MSCT STL files. The CBCT STL files show an overall deviation of 0.07 mm compared to the MSCT STL files. This difference between the scan modalities increases as the volume of anatomical models decreases. The OWLDS is a safe, cost-effective, user-friendly, and highly accurate scanning modality suitable for accuracy evaluation during the manufacturing process of in-house 3D models. For smaller models, high-resolution optical scans are recommended. Full article

The development of advanced diagnostics tools for investigating artworks and monitoring their health state in a non-destructive way is a key point for their preservation and restoration. Non-invasive diagnostic approaches enable the identification of damage often hidden to restorers’ naked eyes, thereby facilitating the planning of appropriate restoration interventions. Here, the combined use of three full-field imaging techniques: shearography, thermography, and structured-light 3D scanning, has been employed as complementary tools for the diagnostics of a panel painting. As a case study, the artwork Consegna della regola Francescana, created by the Neapolitan painter Colantonio around 1445, was analyzed. The integrated application of the mentioned optical imaging techniques allows a comprehensive evaluation of the state of conservation of the work, revealing inserts, nails, and detachments. This synergistic approach also enhanced the interpretation of the results from each individual technique, offering a more complete understanding that would be unattainable with any single method alone. Full article

The evolution of photogrammetry has been significantly influenced by advancements in camera technology, particularly the emergence of spherical cameras. These devices offer extensive photographic coverage and are increasingly utilised in many photogrammetry applications due to their significant user-friendly configuration, especially in their low-cost versions. Despite their advantages, these cameras are subject to high image distortion. This necessitates specialised calibration solutions related to fisheye images, which represent the primary geometry of the raw files. This paper evaluates fisheye calibration processes for the effective utilisation of low-cost spherical cameras, for the purpose of 3D reconstruction and the verification of geometric stability. Calibration optical parameters include focal length, pixel positions, and distortion coefficients. Emphasis was placed on the evaluation of solutions for camera calibration, calibration network design, and the assessment of software or toolboxes that support the correspondent geometry and calibration for processing. The efficiency in accuracy, correctness, computational time, and stability parameters was assessed with the influence of calibration parameters based on the accuracy of the 3D reconstruction. The assessment was conducted using a previous case study of graffiti on an underpass in Wiesbaden, Germany. The robust calibration solution is a two-step calibration process, including a pre-calibration stage and the consideration of the best possible network design. Fisheye undistortion was performed using OpenCV, and finally, calibration parameters were optimized with self-calibration through bundle adjustment to achieve both calibration parameters and 3D reconstruction using Agisoft Metashape software. In comparison to 3D calibration, self-calibration, and a pre-calibration strategy, the two-step calibration process has demonstrated an average improvement of 2826 points in the 3D sparse point cloud and a 0.22 m decrease in the re-projection error value derived from the front lens images of two individual spherical cameras. The accuracy and correctness of the 3D point cloud and the statistical analysis of parameters in the two-step calibration solution are presented as a result of the quality assessment of this paper and in comparison with the 3D point cloud produced by a laser scanner. Full article

Background: Geometric morphometric analysis, a methodology traditionally used in evolutionary studies, offers unprecedented precision in quantifying the morphological traits of human organs and tissues by identifying specific anatomical landmarks. Despite its potential, this approach has not yet been applied in medical or dental research. Materials and Methods: This pilot study analyzed 76 permanent upper first molars (M1) from Italian individuals (38 males and 38 females), selected for their completeness, minimal wear (stage 1), and absence of pathological conditions or non-metric traits. Each individual contributed two contralateral molars: the left molar (Group A) and the right molar (Group B). The molars were scanned using a Sinergia Scan Advanced Plus optical scanner with 5 μm accuracy. The scans were processed with the Dental Scan 7.0 software to generate high-resolution STL files, followed by refinement in Meshlab to preserve the morphological integrity of the 3D models. The geometric morphometric analysis was performed using the Viewbox software, thereby enabling the placement of anatomical landmarks and semilandmarks to quantify and compare molar morphology with exceptional precision. Results: The analysis confirmed that contralateral molars exhibit high morphological similarity, with significantly smaller variability compared to molars from different individuals. Among the specific traits analyzed, the distolingual cusp (hypocone) showed the greatest variation, followed by the mesiolingual cusp (protocone). No significant differences were observed between males and females in the degree of similarity between contralateral molars. Conclusions: This pilot study highlights the potential of geometric morphometric approaches to enhance our understanding of the dental variation between sexes and across human populations, thereby improving clinical applications and advancing toward personalized medicine. Full article

Ultrasonic sensing may become a useful technique for distance measurement and object detection when optical visibility is not available. However, the research on detecting multiple target objects and locating their coordinates is limited. This makes it a valuable topic. Reflection signal data obtained from a single ultrasonic sensor may be just enough for the measurements of distance and reflection strength. On the other hand, if extracted properly, a scanned set of signal data by the same sensor holds a significant amount of information about the surrounding geometries. Evaluating this dataset from a single sensor scanning can be a perfect application for convolutional neural networks (CNNs). This study proposes an imaging technique based on a scanned dataset obtained by a single low-cost ultrasonic sensor. So that images are suitable for desired outputs in a CNN, a 3D printer is converted to an ultrasonic image scanner and automated to perform as a data acquisition system for the desired datasets. A deep learning model demonstrated by this work extracts object features using convolutional neural networks (CNNs) and performs coordinate estimation using regression layers. With the proposed solution, by training a reasonable amount of obtained data, 90% accuracy was achieved in the classification and position estimation of multiple objects with the CNN algorithm as a result of converting the signals obtained from ultrasonic sensors into images. Full article

Background: Cheiloscopy, a forensic technique based on the uniqueness of labial traces, has traditionally relied on analog methods. While simple, these methods present significant limitations in terms of precision and reproducibility. The introduction of 3D technology, specifically high-resolution optical scanners, represents a pivotal advancement in overcoming these challenges. Objective: This pilot study aimed to explore the feasibility and potential advantages of 3D cheiloscopy in forensic science by analyzing its precision and repeatability compared to traditional analog methods. Methods: Two participants were selected as a pilot sample, and their lip impressions were captured using both analog techniques and a high-resolution intraoral scanner (Medit i700). A total of 40 samples were collected, equally distributed among operators with varying levels of experience. Surface deviation analysis was performed to compare the methods. Results: The 3D models demonstrated greater uniformity and resolution compared to the analog impressions, which were more prone to errors caused by material quality or operator pressure. Surface deviation analysis showed an average similarity of 70%, with a standard deviation of 0.229 mm. The digital methods also significantly reduced operator-dependent variability. Conclusions: This pilot study highlights the potential of 3D cheiloscopy to improve precision and standardization in forensic applications. While the small sample size limits the generalizability of the findings, the results provide a foundation for further research with larger and more diverse datasets. Future studies should explore the capability of 3D cheiloscopy to accurately match individuals and further validate its applicability in forensic and clinical contexts. Full article

Registering light detection and ranging (LiDAR) data with optical camera images enhances spatial awareness in autonomous driving, robotics, and geographic information systems. The current challenges in this field involve aligning 2D-3D data acquired from sources with distinct coordinate systems, orientations, and resolutions. This paper introduces a new pipeline for camera–LiDAR post-registration to produce colorized point clouds. Utilizing deep learning-based matching between 2D spherical projection LiDAR feature layers and camera images, we can map 3D LiDAR coordinates to image grey values. Various LiDAR feature layers, including intensity, bearing angle, depth, and different weighted combinations, are used to find correspondence with camera images utilizing state-of-the-art deep learning matching algorithms, i.e., SuperGlue and LoFTR. Registration is achieved using collinearity equations and RANSAC to remove false matches. The pipeline’s accuracy is tested using survey-grade terrestrial datasets from the TX5 scanner, as well as datasets from a custom-made, low-cost mobile mapping system (MMS) named Simultaneous Localization And Mapping Multi-sensor roBOT (SLAMM-BOT) across diverse scenes, in which both outperformed their baseline solutions. SuperGlue performed best in high-feature scenes, whereas LoFTR performed best in low-feature or sparse data scenes. The LiDAR intensity layer had the strongest matches, but combining feature layers improved matching and reduced errors. Full article

This paper presents, for the first time, a rotary actuator functionalized by an inclined disc rotor that serves as a distal optical scanner for endoscopic probes, enabling side-viewing endoscopy in luminal organs using different imaging/analytic modalities such as optical coherence tomography and Raman spectroscopy. This scanner uses a magnetic rotor designed to have a mirror surface on its backside, being electromagnetically driven to roll around the cone-shaped hollow base to create a motion just like a precessing coin. An optical probing beam directed from the probe’s optic fiber is passed through the hollow cone to be incident and bent on the back mirror of the rotating inclined rotor, circulating the probing beam around the scanner for full 360° sideway imaging. This new scanner architecture removes the need for a separate prism mirror and holding mechanics to drastically simplify the scanner design and thus, potentially enhancing device miniaturization and reliability. The first proof-of-concept is developed using 3D printing and experimentally analyzed to reveal the ability of both angular stepping at 45° and high-speed rotation up to 1500 rpm within the biologically safe temperature range, a key function for multimodal imaging. Preliminary optical testing demonstrates continuous circumferential scanning of the laser beam with no blind spot caused by power leads to the actuator. The results indicate the fundamental feasibility of the developed actuator as an endoscopic distal scanner, a significant step to further development toward advancing optical endoscope technology. Full article

Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time. Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. Feature extraction was performed using Tsfresh and ROCKET, which allowed us to capture the patterns in the motor current data corresponding to the geometric features of the machined parts. Our predictive models were trained and validated on a dataset that included motor current readings and corresponding geometric measurements of a mounting rail later used in an engine block. The results showed that the proposed approach enabled the prediction of three geometric features of the mounting rail with an accuracy (MAPE) below 0.61% during the learning phase and 0.64% during the testing phase. These results suggest that our method could reduce the need for post-machining inspections and measurements, thereby reducing production time and costs while maintaining required quality standards. Full article