3D Scanning Research Articles

Towards autonomous robotic THz-based in vivo skin sensing: the PicoBot

Terahertz (THz) light has the unique properties of being very sensitive to water, non-ionizing, and having sub-millimeter depth resolution, making it suitable for medical imaging. Skin conditions including eczema, psoriasis and skin cancer affect a high percentage of the population and we have been developing a THz probe to help with their diagnosis, treatment and management. Our in vivo studies have been using a handheld THz probe, but this has been prone to positional errors through sensorimotor perturbations and tremors, giving spatially imprecise measurements and significant variations in contact pressure. As the operator tires through extended device use, these errors are further exacerbated. A robotic system is therefore needed to tune the critical parameters and achieve accurate and repeatable measurements of skin. This paper proposes an autonomous robotic THz acquisition system, the PicoBot, designed for non-invasive diagnosis of healthy and diseased skin conditions, based on hydration levels in the skin. The PicoBot can 3D scan and segment out the region of interest on the skin’s surface, precisely position (± 0.5/1 mm/degrees) the probe normal to the surface, and apply a desired amount of force (± 0.1N) to maintain firm contact for the required 60 s during THz data acquisition. The robotic automation improves the stability of the acquired THz signals, reducing the standard deviation of amplitude fluctuations by over a factor of four at 1 THz compared to hand-held mode. We show THz results for skin measurements of volunteers with healthy and dry skin conditions on various parts of the body such as the volar forearm, forehead, cheeks, and hands. The tests conducted validate the preclinical feasibility of the concept along with the robustness and advantages of using the PicoBot, compared to a manual measurement setup.

Statistical shape analysis of the Chinese external ear for ergonomic design of in-ear products

3D scanning capture complex ear morphology, but most research focuses on dimensions defined by product design or ergonomic guidelines, often missing crucial 3D details, especially those of ear canal for in-ear product design. This study conducted a statistical shape analysis on the 3D geometry of the cavum concha and the external auditory meatus (EAM) using 1195 scans of Chinese ears. A surface registration method was adopted to standardise and align ear models for shape analysis. Principal component analysis (PCA) generated statistical models of ear shapes, with the most significant variation reflecting the overall width of the cavum concha, explaining 29.63% of the variation. The k-means++ algorithm was employed to classify ear shapes using the first 15 principal component scores, identifying four shape categorisations. Significant variations and shape modes of ear shape were identified, and the derived statistical shape models provide essential 3D references for the ergonomic design of ear-related products.

Design and development of a customized 3D-printed assistive device using modular 3D blocks

Purpose 3D printing enables the production of customizable, cost-effective, and reproducible items, making it a promising approach for manufacturing assistive devices. This study aims to develop customized 3D-printed assistive devices using 3D blocks. Methods A 3D scanner was used to scan the limbs and trunks where the devices would be worn. The study utilized 3D blocks capable of undergoing subdivision surfaces to match the scanned external appearance of limbs and trunks. The mass-spring model and Gauss-Newton method were applied to optimize the subdivision surfaces, ensuring a better fit for users’ hand shapes. Additionally, 3D blocks were used as design units for blending-based morphing, generating diverse 3D patterns. Results The proposed approach successfully enabled real-time manufacturing of customized external appearances for assistive devices. The resulting designs met usability, functionality, and aesthetic requirements. Usability testing, conducted using the Quebec User Evaluation of Satisfaction with Assistive Technology, demonstrated high satisfaction scores, confirming the effectiveness of 3D blocks in customizing assistive devices. Conclusions By integrating 3D scanning and printing technologies, this study highlights the feasibility of using reverse engineering to develop personalized assistive devices. The findings suggest that the proposed method enhances user satisfaction and provides a practical approach to assistive device customization.

Fixed-focus laser triangulation simultaneously measures the morphology and color of object

Abstract Simultaneously measuring the surface morphology and color of a sample is crucial for full-color 3D printing and digitization of cultural artifacts. However, traditional methods are susceptible to the variations in the measurement angle and illumination condition, making it difficult to balance the color fidelity and spatial accuracy. Here, we propose a laser triangulation method that is implemented with a fixed focus, dark-field illumination, and data-driven spectral classification. With a fixed focus, this method measures the height of surface by analyzing the shape of reflected light spot. The dark-field illumination diminishes the background contributed by the specular reflection of white light, enabling an accurate spectral measurement. The data-driven spectral classification algorithm establishes color dataset for each sample, and ensures a precise color recognition through Principal component analysis (PCA) dimensionality reduction and K-nearest neighbor (KNN) classification. In our experiment, this method achieved an axial resolution of 5.1μm. The color classification accuracy was as high as 99.79% on ColorChecker cards and 96.03% on Pantone color match cards. Two samples were reconstructed and evaluated to validate this method, the Mean
Absolute Error (MAE) of the morphology measurements did not exceed 25μm, and the color difference (CIE2000) does not exceed 1.0, confirming its ability to accurately measure the surface morphology and color simultaneously.surface morphology and color simultaneously.

A Refined Approach to Segmenting and Quantifying Inter-Fracture Spaces in Facial Bone CT Imaging

The human facial bone is made up of many complex structures, which makes it challenging to accurately analyze fractures. To address this, we developed advanced image analysis software which segments and quantifies spaces between fractured bones in facial CT images at the pixel level. This study used 3D CT scans from 1766 patients who had facial bone fractures at a university hospital between 2014 and 2020. Our solution included a segmentation model which focuses on identifying the gaps created by facial bone fractures. However, training this model required costly pixel-level annotations. To overcome this, we used a stepwise annotation approach. First, clinical specialists marked the bounding boxes of fracture areas. Next, trained specialists created the initial pixel-level unrefined ground truth by referencing the bounding boxes. Finally, we created a refined ground truth to correct human errors, which helped improve the segmentation accuracy. Radiomics feature analysis confirmed that the refined dataset had more consistent patterns compared with the unrefined dataset, showing improved reliability. The segmentation model showed significant improvement in the Dice similarity coefficient, increasing from 0.33 with the unrefined ground truth to 0.67 with the refined ground truth. This research introduced a new method for segmenting spaces between fractured bones, allowing for precise pixel-level identification of fracture regions. The model also helped with quantitative severity assessment and enabled the creation of 3D volume renderings, which can be used in clinical settings to develop more accurate treatment plans and improve outcomes for patients with facial bone fractures.

How to make teaching of wood anatomy more engaging with 3D data

Wood is a highly heterogeneous material with a variable and three-dimensional (3D) anatomy at the microscopic level. Research and application of wood depend on well-educated individuals, who understand the wood anatomy. The teaching and learning of that complex structure are challenging with common teaching resources, which are mostly based on two-dimensional microscopy images. Innovative teaching materials may involve 3D data provided by micro-computed tomography (micro-CT). Using 3D data of wood, this article suggests approaches to make teaching and learning of wood anatomy more engaging. Whereas 3D visualizations can be added as a new resource to teaching presentations, digital 3D models of wood features can be incorporated into virtual data libraries allowing students to move freely through the 3D structure. These models can also be printed using additive manufacturing providing hands-on material in class. These teaching materials have the potential to become a valuable and future-oriented educational toolkit for promoting students’ learning experience and motivation. To encourage the use of 3D data in teaching, 3D data of selected anatomical features of softwoods and hardwoods are provided along with the article.

Enhancing dental education with a 3D point cloud comparison and augmented reality for auto-evaluation of fixed prosthodontic practice: An in vitro study.

Traditional fixed prosthodontic training evaluations are time-consuming and subjective. This study aimed to introduce and evaluate a novel 3D auto-evaluate tooth preparation with an augmented reality (3DAR) visualization algorithm to enhance dental education for students and improve the efficiency of fixed prosthodontic training evaluations. Fifty maxillary central incisors and first molars prepared by 50 dental students on typodont models were scanned with a 3D scanner to capture STL files and evaluated using the 3DAR algorithm, which calculated Euclidean distances and root mean square error (RMSE) for accuracy assessment and assigned scores based on RMSE, using an augmented reality (AR) app for interactive evaluation and visualization. These scores were compared to manual scoring with computer assistance (MSCA method), which also used RMSE but required manual alignment and model scoring. Intrarater and interrater reliability of the 3DAR scoring method was assessed using intraclass correlation coefficients (ICC) and compared with the MSCA method. Additionally, the feasibility of 3DAR was evaluated based on evaluation time and user satisfaction. The 3DAR method demonstrated good-to-excellent interrater agreement (ICC = 0.75-0.95) and perfect intrarater reliability (ICC = 1), while the MSCA method showed moderate-to-good reliability (ICC = 0.74-0.89). 3DAR significantly reduced evaluation time (10.514 s vs. 2 h required for MSCA) and received high user satisfaction ratings (average score = 4.66±0.24). The 3DAR algorithm offers a reliable and efficient assessment method for prosthodontic training. It showed strong agreement with traditional methods, significantly reduced evaluation time, and achieved high user satisfaction. The integration of a 3D augmented reality-based auto-evaluation algorithm into tooth preparation training enhances reliability and provides interactive, real-time feedback on performance, highlighting its potential to advance dental education practices.

Single right sided traumatic avulsion fracture of both ASIS and AIIS: case review

Introduction and importance: Simultaneous avulsion fractures of the anterior superior iliac spine (ASIS) and anterior inferior iliac spine (AIIS) are rare, typically resulting from intense muscular contractions in athletes. Accurate diagnosis requires thorough examination and imaging. Case presentation: A 29-year-old male sustained right-sided ASIS and AIIS avulsion fractures from a road traffic accident. Diagnosis was confirmed via plain radiographs and 3D CT scans. The patient underwent surgical fixation with cannulated cancellous screws. He fully recovered and resumed pre-injury sports activity within 5 months. Clinical discussion: ASIS and AIIS avulsion fractures are uncommon, with simultaneous occurrences being even rarer. Proper diagnosis and surgical intervention are crucial, especially in active patients with significant displacement. Conclusion: Surgical treatment using cannulated cancellous screws led to complete recovery and return to sports activity in this case, highlighting the effectiveness of this approach for managing complex avulsion fractures.

In-vitro accuracy of the virtual patient model with maxillomandibular relationship at centric occlusion using 3D-printed customized transfer key

ObjectiveThis study aimed to create a 3D-printed customized transfer key and evaluate the accuracy of the virtual patient model with maxillomandibular relationship at centric occlusion using the transfer key.MethodsA 3D-printed transfer key was designed, combining facial and intraoral (IOS) scans. The design included components that recorded the 3D upper and lower arch at centric occlusion. The virtual patient model image was generated in-vitro using a phantom head with soft tissue simulation. Accuracy was assessed by superimposing the 3D scans with reference CBCT images and analyzing trueness and precision using root mean square (RMS) deviations.ResultsThe transfer key included an intra-oral part that acts as an anterior deprogrammer to record the relationship of two dental arches at centric occlusion (CO) and an extra-oral with a rotatable cross-shaped design with two arms for locating the facial midline and the two pupils connecting line. Superimposition demonstrated high trueness (RMS: 0.51 mm for the arch regions, 0.69 mm for the whole head region, 0.85 mm in the face region) and precision (RMS: 0.41 mm for the arch regions, 0.52 mm for the entire head, 0.63 mm in the face region) significantly (p < 0.05). Minimal deviations were observed in critical areas, including the tooth and lip position, indicating that the virtual patient model was closely aligned with the CBCT reference. The dental arches achieved the highest accuracy, while slight deviations were noted in the facial regions.ConclusionsThe 3D-printed customized transfer key effectively enhanced the virtual patient model’s accuracy, surpassing traditional trueness and precision methods. This novel approach offers a streamlined, patient-friendly solution for digital dental workflows.

Digital 3D reconstructions of synagogues for an innovative approach on Jewish architectural heritage in East Central Europe

Digital 3D reconstructions of synagogues for an innovative approach on Jewish architectural heritage in East Central Europe

3D scanner's potential as a novel tool for lymphedema measurement in mouse hindlimb models.

Lymphedema is characterized by persistent swelling due to impaired lymphatic function and presents significant challenges in both research and clinical settings. Traditional contact-based measurement techniques such as paw thickness and circumferential measurements using calipers or silk thread are useful but limited by observer variability and measurement accuracy. Non-contact methods, including various imaging techniques, offer improvements but often at higher cost and complexity. In this study, we address the need for a more reliable, cost-effective, and non-invasive method for assessing lymphedema in mouse models. Here we show that 3D scanning technology can enhance the measurement of lymphedema in a mouse hindlimb model. Our results indicate that 3D scanners provide more consistent measurements with lower variability compared with conventional methods and without the need for direct contact, which could potentially alter the measurement outcomes. The findings of this study suggest that 3D scanning could replace traditional methods, offering a more standardized and less subjective tool for lymphedema research in the near future. This technology would not only improve upon conventional methods but also extend the capabilities for detailed anatomical analyses in small animal models, which could have implications for other areas of biomedical research.

Predictors and Implications of Myocardial Injury in Intracerebral Hemorrhage.

Myocardial injury, indicated by an elevation of high-sensitive cardiac Troponin (hs-cTnT), is afrequent stroke-related complication. Most studies investigated patients with ischemic stroke, but only little is known about its occurrence in patients with intracerebral hemorrhage (ICH). This study aimed to assess the frequency, predictors, and implications of myocardial injury in ICH patients. Our retrospective analysis included 322 ICH patients. We defined myocardial injury as an elevation of hs-cTnT above the 99th percentile (i.e. 14 ng/L). Acute myocardial injury was defined as either achanging pattern of > 50% within 24 h or an excessive elevation of initial hs-cTnT (> 52 ng/L). 3D brain scans were assessed for ICH visually and quantitatively by adeep learning algorithm. Multiple regression models and Voxel-based Lesion-Symptom Mapping (VLSM) were applied. 63.0% (203/322) of patients presented with myocardial injury, which was associated with more severe strokes and worse outcomes during the in-hospital phase (P < 0.01). Acute myocardial injury occurred in 24.5% (79/322) of patients. The only imaging finding associated with acute myocardial injury was midline shift (69.8% vs. 44.6% for normal or stable hs-cTnT, P < 0.01), which also independently predicted it (odds ratio 3.29, confidence interval 1.38-7.87, P < 0.01). In contrast, VLSM did not identify any specific brain region significantly associated with acute myocardial injury. Acute myocardial injury did not correlate with preexisting cardiac diseases; however, the frequency of adverse cardiac events was higher in the acute myocardial injury group (11.4% vs.4.1% in patients with normal and/or stable patterns of hs-cTnT, P < 0.05). Myocardial injury occurs frequently in ICH and is linked to poor outcomes. Acute myocardial injury primarily correlates to space-occupying effects of ICH but is less dependent on premorbid cardiac status. Nonetheless, it is associated with ahigher rate of adverse cardiac events.

Constructing relative spatial relationships of large-area objects using time-of-flight sensing and achieving multidimensional evaluation

3D scanning can construct comprehensive information about objects. However, scanning scenes at the meter scale is costly and inefficient. For large-area objects with distinctive physical attributes or tasks emphasizing internal relational mapping, there is value in taking a few sampling points to establish the relative relationships of objects. In this work, we used a time-of-flight camera for point data construction, demonstrating the use of the method on a wall. Meanwhile, a method to achieve a multi-dimensional assessment of wall flatness using relative relationships with only one acquisition is demonstrated, which has the potential for applications integrated with robotic construction.

Ultra-small spectral confocal displacement sensors based on GRIN lenses

Spectral confocal displacement sensors have been widely used in various precision measurement fields such as aerospace, biology, and medicine due to their advantages of high accuracy, non-contact, fast response, and high resolution. In this paper, a new method of spectral confocal measurement of a ultra-compact probe based on a GRIN lens, to our knowledge, is proposed. Through ray tracing analysis, it is found that the axial dispersion is close to linear in a specific wavelength range, and a theoretical model of spectral confocal measurement with the GRIN lens is deduced. A GRIN lens with a diameter of 1 mm and a length of 6.59 mm was prepared by the ion-exchange method and used as a dispersive objective lens in a homemade spectral confocal measurement system. The system was calibrated to have an axial measurement range of 440 µm, an axial resolution better than 0.5 µm, a maximum standard deviation of 0.749 µm, and a relative error of less than 2%. In addition, the system was successfully applied to 3D surface contour scanning, demonstrating its potential for 3D scanning. The results show that the system has the advantages of simple structure, low cost, easy integration, and excellent performance.

LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification

Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentation frameworks in medical imaging often rely on fully annotated datasets. However, for lymph node segmentation, these datasets are typically small due to the extensive time and expertise required to annotate the numerous lymph nodes in 3D CT scans. Weakly-supervised learning, which leverages incomplete or noisy annotations, has recently gained interest in the medical imaging community as a potential solution. Despite the variety of weakly-supervised techniques proposed, most have been validated only on private datasets or small publicly available datasets. To address this limitation, the Mediastinal Lymph Node Quantification (LNQ) challenge was organized in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). This challenge aimed to advance weakly-supervised segmentation methods by providing a new, partially annotated dataset and a robust evaluation framework. A total of 16 teams from 5 countries submitted predictions to the validation leaderboard, and 6 teams from 3 countries participated in the evaluation phase. The results highlighted both the potential and the current limitations of weakly-supervised approaches. On one hand, weakly-supervised approaches obtained relatively good performance with a median Dice score of 61.0%. On the other hand, top-ranked teams, with a median Dice score exceeding 70%, boosted their performance by leveraging smaller but fully annotated datasets to combine weak supervision and full supervision. This highlights both the promise of weakly-supervised methods and the ongoing need for high-quality, fully annotated data to achieve higher segmentation performance.

Morphology-Based In-Ovo Sexing of Chick Embryos Utilizing a Low-Cost Imaging Apparatus and Machine Learning

The routine culling of male chicks in the laying hen industry raises significant ethical, animal welfare, and sustainability concerns. Current methods to determine chick embryo sex before hatching are costly, time-consuming, and invasive. This study aimed to develop a low-cost, non-invasive solution to predict chick embryo sex before hatching using the morphological features of eggs. A custom imaging apparatus was created using a smartphone and light box, enabling consistent image capture of chicken eggs. Egg length, width, area, eccentricity, and extent were measured, and machine learning models were trained to predict chick embryo sex. The wide neural network model achieved the highest accuracy of 88.9% with a mean accuracy of 81.5%. Comparison of the imaging apparatus to a high-cost industrial 3D scanner demonstrated comparable accuracy in capturing egg morphology. The findings suggest that this method can contribute to the prevention of up to 6.2 billion male chicks from being culled annually by destroying male embryos before they develop the capacity to feel pain. This approach offers a feasible, ethical, and scalable alternative to current practices, with potential for further improvements in accuracy and adaptability to different industry settings.

3D imaging of underwater scanning photon counting lidar based on multiscale spatio-temporal resolution

This manuscript presents an underwater scanning photon counting lidar system specifically designed for the 3D imaging of underwater targets. A multiscale spatio-temporal resolution method is proposed to enhance the accuracy and resolution of 3D scanning imaging. Signal extraction is achieved through macro pulse accumulation number and macro time resolution, based on the spatio-temporal correlation constrained by relative signal intensity difference factor. Subsequently processing focuses exclusively on the photon-counting events extracted in the previous step. By employing micro pulse accumulation number and micro time resolution, each pixel is expanded into multiple pixels, thereby improving timing precision. This not only enhances imaging accuracy but also enables the detection of more detailed information about the target. The reconstructed images of the resolution plate located approximately 3.5 meters away demonstrate that both the imaging accuracy and resolution are within 10.0 mm. In addition, high-performance 3D reconstruction of a coral model located approximately 4 meters away with complex surface shape is also realized, where each branch of the coral can be distinctly identified. It is verified that the developed lidar system has the ability of high-performance 3D imaging for underwater targets. This lidar system will play an important role in the field of fine mapping of seabed topography and underwater target detection and recognition.

Modeling of Direct Energy Deposition for Wire Laser Additive Manufacturing

Abstract This work discusses the relevance of direct energy deposition (DED) and its classifications. Different types of DED processes are discussed, including their main parameters and issues. Two experiments were carried out, named single bead and rectangular prism, for the purpose of this research. These were built with a hot wire and laser DED system, where experimental thermal data were obtained, later geometric information was obtained via a 3D scan. Limitations of the equipment used as well as observed defects in the material deposition are discussed based on the experimental data. FEA models were developed to duplicate the experiments, which included a detailed geometry of the single bead. Two modifications to the bead geometry are presented and evaluated, where it is was concluded that a semi-circular bead approximation provides better results than if a rectangular one is assumed. This led to the definition of a thermal and structural equivalent model of the single bead, which was the basis for the numerical work of the rectangular prism. The results obtained for the latter show good agreement with the thermal results, although differences in the structural results are perceptible.

Novel sustainable, smart, and multifunctional 4D-printed nanocomposites with reprocessing and shape memory capabilities

Abstract The present paper explores the development of novel recyclable and reprocessable nanocomposites with enhanced shape memory (SM) capability Digital Light Processing 3D printing technology. More specifically, the developed Covalent Adaptable Network is based on polyurethane containing Diels Alder bonds reinforced with carbon nanotubes (CNTs), where the dynamic bonds enable recyclability and reprocessability, whereas CNT addition allows obtaining electrically conductive nanocomposites. In this sense, the nanocomposites exhibited significant Joule heating capabilities, which were used to trigger the SM cycle.&amp;#xD;First, CNT contents and thermal treatments were tuned to optimize SM capabilities in a conventional oven, seeking for obtaining a stable temporary shape at room temperature. Then, the SM capabilities triggered by Joule heating were characterized. Here, the optimized nanocomposites showed excellent shape fixity and recovery ratios (both above 95 %) when triggering the SM by the Joule effect. This heating method was proven to be low energy-consuming (around 1 W), as well as allowing fast, remote, and selective activation, being the latter the ability to trigger the SM in a specific area of the specimen as desired, which was demonstrated with a hand-like proof-of-concept by selectively recovering the permanent shape of each finger.&amp;#xD;Finally, the 3D-printed specimens were turned into powder and reprocessed using a powder processing tool, obtaining a still electrically conductive part with a different geometry given the DA adduct formations.&amp;#xD;In summary, the multifunctional and smart capabilities of the developed nanocomposites make them suitable for applications such as soft robotics or actuators with an extended useful life, promoting sustainability.&amp;#xD;

Polyionic Liquid/Poly(3,4-ethylenedioxythiophene)-Based Mixed Ionic and Electronic Conductive Hydrogel for Digital Light Processing 3D Printing

Polyionic Liquid/Poly(3,4-ethylenedioxythiophene)-Based Mixed Ionic and Electronic Conductive Hydrogel for Digital Light Processing 3D Printing