An Overview on Image-Based and Scanner-Based 3D Modeling Technologies

Surface reconstruction and thickness error calculation of optical components with a complex curved surface

The increasing demand for free-form irregular optical components in both military and civilian sectors has made the inspection of such unique shapes a central challenge that hinders their production and use. In particular, the shape and thickness errors of low- and medium-precision components thermally pressed from flat optical materials are greater than those of hard brittle optical components fabricated by subtractive manufacturing, and the resulting impact on human vision is more severe. Reasonable, convenient, efficient, and accurate 3D scanning and data processing for surface reconstruction that combines application scenarios and batch manufacturing needs are urgently needed. Based on the principles of optical ray tracing and triangulation processing, the sampling and calculation of optical path thickness proposed in this paper effectively establish a theoretical model for macroscopic distortion, providing a reasonable solution for distortion correction, batch manufacturing of free-form surface pressing formed components, and defect repair.

Objective assessment of simulated non-carious cervical lesion by tridimensional digital scanning - An in vitro study

OBJECTIVE

Clinical assessment of progression of non-carious cervical lesions (NCCLs) is currently based on subjective methods. We hypothesize that 3D digital intraoral scanners (IOS) can provide quantitative outcomes for objective measuring and monitoring of NCCLs. This in vitro study verified the reliability of IOS to monitor dental structure loss of simulated NCCLs, in comparison to a reference bench-top 3D optical profilometer (BTS).

METHODS

NCCLs of different severity levels (early, moderate, or severe, n = 150) were simulated in a preceding study. Impressions of the lesions were taken and scanned with both BTS (ProScan; Scantron) and IOS (TRIOS4; 3Shape). Generated 3D images were analyzed for volumetric tooth loss (mm3) by superimposition followed by subtraction analysis. ProForm (Scantron) and WearCompare (Leeds Digital Dentistry) software were used in association to BTS and IOS, respectively. Agreement was assessed using intraclass correlation coefficient (ICC, alpha=0.05) and Bland-Altman plots.

RESULTS

ICC (confidence interval at 95 %) between IOS and BTS for all data combined was 0.962 (0.942-0.973), showing excellent reliability. Subset analyses showed that NCCLs with lower volume loss (early- and moderate-stage lesions) resulted in moderate ICCs, whereas severe lesions showed excellent ICC. Bland-Altman plots demonstrated general good agreement, with narrower limits for early stage-lesions.

CONCLUSION

IOS data demonstrated good agreement to BTS, when measuring tooth structure loss in simulated NCCLs, with particularly higher ICC in more severe lesions. Considering the accessibility and ease-of-use, IOS showed to be a good alternative for the objective assessment of NCCLs in vitro.

CLINICAL SIGNIFICANCE

3D intraoral scanners' accessibility and objectivity make them potentially valuable tools for assessing and monitoring NCCLs.

The Role of Cone Beam Computed Tomography in Periodontology: From 3D Models of Periodontal Defects to 3D-Printed Scaffolds

The treatment of osseous defects around teeth is a fundamental concern within the field of periodontology. Over the years, the method of grafting has been employed to treat bone defects, underscoring the necessity for custom-designed scaffolds that precisely match the anatomical intricacies of the bone cavity to be filled, preventing the formation of gaps that could allow the regeneration of soft tissues. In order to create such a patient-specific scaffold (bone graft), it is imperative to have a highly detailed 3D representation of the bone defect, so that the resulting scaffold aligns with the ideal anatomical characteristics of the bone defect. In this context, this article implements a workflow for designing 3D models out of patient-specific tissue defects, fabricated as scaffolds with 3D-printing technology and bioabsorbable materials, for the personalized treatment of periodontitis. The workflow is based on 3D modeling of the hard tissues around the periodontal defect (alveolar bone and teeth), scanned from patients with periodontitis. Specifically, cone beam computed tomography (CBCT) data were acquired from patients and were used for the reconstruction of the 3D model of the periodontal defect. The final step encompasses the 3D printing of these scaffolds, employing Fused Deposition Modeling (FDM) technology and 3D-bioprinting, with the aim of verifying the design accuracy of the developed methodοlogy. Unlike most existing 3D-printed scaffolds reported in the literature, which are either pre-designed or have a standard structure, this method leads to the creation of highly detailed patient-specific grafts. Greater accuracy and resolution in the macroarchitecture of the scaffolds were achieved during FDM printing compared to bioprinting, with the standard FDM printing profile identified as more suitable in terms of both time and precision. It is easy to follow and has been successfully employed to create 3D models of periodontal defects and 3D-printed scaffolds for three cases of patients, proving its applicability and efficiency in designing and fabricating personalized 3D-printed bone grafts using CBCT data.

Automation in Dentistry with Mechanical Drills and Lasers for Implant Osteotomy: A Narrative-Scoping Review

The popularity of implants is increasing with the aging population requiring oral-dental rehabilitation. There are several critical steps in the implant workflow, including case selection, implant design, surgical procedure, biological tissue responses, and functional restoration. Among these steps, surgical osteotomy procedures are a crucial determinant of clinical success. This brief review was aimed at outlining the current state of the field in automation-assisted implant surgical osteotomy technologies. A broad search of the literature was performed to identify current literature. The results are outlined in three broad categories: semi-automated static (image-guided) or dynamic (navigation-assisted) systems, and fully-automated robotic systems. As well as the current mechanical rotary approaches, the literature supporting the use of lasers in further refinement of these approaches is reviewed. The advantages and limitations of adopting autonomous technologies in practical clinical dental practices are discussed. In summary, advances in clinical technologies enable improved precision and efficacious clinical outcomes with implant dentistry. Hard-tissue lasers offer further advancements in precision, improved biological responses, and favorable clinical outcomes that require further investigation.

Part2Point: A Part-Oriented Point Cloud Reconstruction Framework

Three-dimensional object modeling is necessary for developing virtual and augmented reality applications. Traditionally, application engineers must manually use art software to edit object shapes or exploit LIDAR to scan physical objects for constructing 3D models. This is very time-consuming and costly work. Fortunately, GPU recently provided a cost-effective solution for massive data computation. With GPU support, many studies have proposed 3D model generators based on different learning architectures, which can automatically convert 2D object pictures into 3D object models with good performance. However, as the demand for model resolution increases, the required computing time and memory space increase as significantly as the parameters of the learning architecture, which seriously degrades the efficiency of 3D model construction and the feasibility of resolution improvement. To resolve this problem, this paper proposes a part-oriented point cloud reconstruction framework called Part2Point. This framework segments the object's parts, reconstructs the point cloud for individual object parts, and combines the part point clouds into the complete object point cloud. Therefore, it can reduce the number of learning network parameters at the exact resolution, effectively minimizing the calculation time cost and the required memory space. Moreover, it can improve the resolution of the reconstructed point cloud so that the reconstructed model can present more details of object parts.

Edge detection using fast pixel based matching and contours mapping algorithms

Current methods of edge identification were constrained by issues like lighting changes, position disparity, colour changes, and gesture variability, among others. The aforementioned modifications have a significant impact, especially on scaled factors like temporal delay, gradient data, effectiveness in noise, translation, and qualifying edge outlines. It is obvious that an image's borders hold the majority of the shape data. Reducing the amount of time it takes for image identification, increase gradient knowledge of the image, improving efficiency in high noise environments, and pinpointing the precise location of an image are some potential obstacles in recognizing edges. the boundaries of an image stronger and more apparent locate those borders in the image initially, sharpening it by removing any extraneous detail with the use of the proper filters, followed by enhancing the edge-containing areas. The processes involved in recognizing edges are filtering, boosting, recognizing, and localizing. Numerous approaches have been suggested for the previously outlined identification of edges procedures. Edge detection using Fast pixel-based matching and contours mappingmethods are used to overcome the aforementioned restrictions for better picture recognition. In this article, we are introducing the Fast Pixel based matching and contours mapping algorithms to compare the edges in reference and targeted frames using mask-propagation and non-local techniques. Our system resists significant item visual fluctuation as well as copes with obstructions because we incorporate input from both the first and prior frames Improvement in performance in proposed system is discussed in result section, evidences are tabulated and sketched. Mainly detection probabilities and detection time is remarkably reinforced Effective identification of such things were widely useful in fingerprint comparison, medical diagnostics, Smart Cities, production, Cyber Physical Systems, incorporating Artificial Intelligence, and license plate recognition are conceivable applications of this suggested work.

CBCT-Based Design of Patient-Specific 3D Bone Grafts for Periodontal Regeneration

The purpose of this article is to define and implement a methodology for the 3D design of customized patient-specific scaffolds (bone grafts) for the regeneration of periodontal tissues. The prerequisite of the proposed workflow is the three-dimensional (3D) structure of the periodontal defect, i.e., the 3D model of the hard tissues (alveolar bone and teeth) around the periodontal damage, which is proposed to be generated via a segmentation and 3D editing methodology using cone beam computed tomography (CBCT) data. Two types of methodologies for 3D periodontal scaffold (graft) design are described: (i) The methodology of designing periodontal defect customized block grafts and (ii) the methodology of designing extraction socket preservation customized grafts. The application of the proposed methodology for the generation of a 3D model of the hard tissues around periodontal defects of a patient using a CBCT scan and the 3D design of the two aforementioned types of scaffolds for personalized periodontal regenerative treatment shows promising results. The outputs of this work will be used as the basis for the 3D printing of bioabsorbable scaffolds of personalized treatment against periodontitis, which will simultaneously be used as sustained-release drug carriers.

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

An intelligent transportation system is one of the fundamental goals of the smart city concept. The Internet of Things (IoT) concept is a basic instrument to digitalize and automatize the process in the intelligent transportation system. Digitalization via the IoT concept enables the automatic collection of data usable for management in the transportation system. The IoT concept includes a system of sensors, actuators, control units and computational distribution among the edge, fog and cloud layers. The study proposes a taxonomy of sensors used for monitoring tasks based on motion detection and object tracking in intelligent transportation system tasks. The sensor's taxonomy helps to categorize the sensors based on working principles, installation or maintenance methods and other categories. The sensor's categorization enables us to compare the effectiveness of each sensor's system. Monitoring tasks are analyzed, categorized, and solved in intelligent transportation systems based on a literature review and focusing on motion detection and object tracking methods. A literature survey of sensor systems used for monitoring tasks in the intelligent transportation system was performed according to sensor and monitoring task categorization. In this review, we analyzed the achieved results to measure, sense, or classify events in intelligent transportation system monitoring tasks. The review conclusions were used to propose an architecture of the universal sensor system for common monitoring tasks based on motion detection and object tracking methods in intelligent transportation tasks. The proposed architecture was built and tested for the first experimental results in the case study scenario. Finally, we propose methods that could significantly improve the results in the following research.

Three-Dimensional Immersion Scanning Technique: A Scalable Low-Cost Solution for 3D Scanning Using Water-Based Fluid

Three-dimensional scanning technology has been traditionally used in the medical and engineering industries, but these scanners can be expensive or limited in their capabilities. This research aimed to develop low-cost 3D scanning using rotation and immersion in a water-based fluid. This technique uses a reconstruction approach similar to CT scanners but with significantly less instrumentation and cost than traditional CT scanners or other optical scanning techniques. The setup consisted of a container filled with a mixture of water and Xanthan gum. The object to be scanned was submerged at various rotation angles. A stepper motor slide with a needle was used to measure the fluid level increment as the object being scanned was submerged into the container. The results showed that the 3D scanning using immersion in a water-based fluid was feasible and could be adapted to a wide range of object sizes. The technique produced reconstructed images of objects with gaps or irregularly shaped openings in a low-cost fashion. A 3D printed model with a width of 30.7200 ± 0.2388 mm and height of 31.6800 ± 0.3445 mm was compared to its scan to evaluate the precision of the technique. Its width/height ratio (0.9697 ± 0.0084) overlaps the margin of error of the width/height ratio of the reconstructed image (0.9649 ± 0.0191), showing statistical similarities. The signal-to-noise ratio was calculated at around 6 dB. Suggestions for future work are made to improve the parameters of this promising, low-cost technique.