Evaluating the accuracy of hand models obtained from two 3D scanning techniques

Multi-objective optimization for enhanced digitalization in direct 3D printing: an application in dentistry

OBJECTIVE

This study aims to mitigate variances between scanned STL files and original models to limit divergence from reference files and ensure dental appliance manufacture accuracy. The study also attempts to optimize STL mesh triangles to improve digital model quality and detail while balancing memory usage and accuracy. It also examines how external factors like scan distance (SD), scan angle (SA), and light intensity (LI) affect STL file quality and accuracy. The research also optimizes scanning parameters utilizing a multi-objective optimization approach to find the optimal combination of SD, SA, and LI to minimize deviation, triangles and time consumed altogether, improving 3D printing efficiency and accuracy.

MATERIALS AND METHODS

An optimal combination for experiments is developed using response surface methodology with varying ranges of SD, SA, and LI to generate 20 runs. The study used a denture to develop scanned STL files at these different parametric combinations, evaluating the resulting output deviation, number of triangles and time. Predictive model for deviation is then created and processed using the multi-objective Non- dominated sorting Genetic algorithm II to minimize deviation, triangles and time consumed.

RESULTS

The results of the study demonstrate the significance of the developed model for deviation only using regression and for all three using ANN. As indicated by ANOVA analysis revealing a p-value less than 0.05, affirming regression model statistical significance. Optimization results states SD of 5.3621 inch, SA 82.1746 degree and LI 15.2456 W/m2 with AD 0.1964 NT 27,811 and time consumed 89.2203 s as resulting optimized parameters altogether. A pareto front combinations is developed to select combination based on designated requirement. Additionally, optimized parameters are tested experimentally for validation.

CONCLUSIONS

The accuracy of file is heavily contingent upon the quality of the STL mesh derived from the process. This mesh typically requires preprocessing due to its unorganized structure, which not only compromises accuracy but also incurs additional time due to inefficiencies in mesh structure. Furthermore, while increasing the number of triangles in the mesh provides higher resolution and accuracy, it also demands greater memory allocation. Thus, achieving a balance between memory usage and the number of triangles is imperative.

CLINICAL RELEVANCE

Direct 3D printing streamlines dental fabrication by using patient-specific scanned STL files to create dental appliances. This method saves time, improves efficiency, and eliminates multi-stage cast generation. The scanned STL files, originally produced from point cloud data processed by surface reconstruction, must be accurate. Unorganized STL meshes require preprocessing, which reduces accuracy and increases time. Adding mesh triangles improves resolution and accuracy, but it requires more memory. Thus, memory utilization and triangle count must be balanced with time consumed. Fixing these issues provides high-quality, accurate dental restorations, increasing patient outcomes and digital dentistry. Additionally, it provides practioners to develop freedom constraints devices with more effectiveness.

Comparative evaluation of Artec Leo hand-held scanner and iPad Pro for 3D scanning of cervical and craniofacial data: assessing precision, accuracy, and user experience

AIM

This study compares the precision, accuracy, and user experience of 3D body surface scanning of human subjects using the Artec Leo hand-held scanner and the iPad Pro as 3D scanning devices for capturing cervical and craniofacial data. The investigation includes assessing methods for correcting 'dropped head syndrome' during scanning, to demonstrate the ability of the scanner to be used to reconstruct body surface of patients.

METHODS

Eighteen volunteers with no prior history of neck weakness were scanned three times in three different positions, using the two different devices. Surface area, scanning time, and participant comfort scores were evaluated for both devices. Precision and accuracy were assessed using Mean Absolute Deviation (MAD), Mean Absolute Percentage Error (MAPE), and Intra-Class Correlation Coefficients (ICC).

RESULTS

Surface area comparisons revealed no significant differences between devices and positions. Scanning times showed no significant difference between devices or positions. Comfort scores varied across positions. MAD analysis identified chin to chest measurements as having the highest variance, especially in scanning position 3. However, no statistical differences were found. MAPE results confirmed accuracy below 5% error for both devices. ICC scores indicated good reliability for both measurement methods, particularly for chin to chest measurements in positions 1 and 3.

CONCLUSION

The iPad Pro using the Qlone app demonstrates a viable alternative to the Artec Leo, particularly for capturing head and neck surface area within a clinical setting. The scanning resolution, with an error margin within ±5%, is consistent with clinically accepted standards for orthosis design, where padding and final fit adjustments allow for bespoke devices that accommodate patient comfort. This study highlights the comparative performance of the iPad, as well as suggests two methods which can be used within clinics to correct head drop for scanning.

Three-dimensional imaging of the forearm and hand: A comparison between two 3D imaging systems

The conventional treatment for distal radius fractures typically involves immobilization of the injured extremity using a conventional forearm cast. These casts do cause all sorts of discomfort during wear and impose life-style restrictions on the wearer. Personalized 3D printed splints, designed using three-dimensional (3D) imaging systems, might overcome these problems. To obtain a patient specific splint, commercially available 3D camera systems are utilized to capture patient extremities, generating 3D models for splint design. This study investigates the feasibility of utilizing a new camera system (SPENTYS) to capture 3D surface scans of the forearm for the design of 3D printed splints. In a prospective observational cohort study involving 17 healthy participants, we conducted repeated 3D imaging using both the new (SPENTYS) and a reference system (3dMD) to assess intersystem accuracy and repeatability. The intersystem accuracy of the SPENTYS system was determined by comparison of the 3D surface scans with the reference system (3dMD). Comparison of consecutive images acquired per device determined the repeatability. Feasibility was measured with system usability score questionnaires distributed among professionals. The mean absolute difference between the two systems was 0.44 mm (SD:0.25). The mean absolute difference of the repeatability of the reference -and the SPENTYS system was respectively 0.40 mm (SD: 0.30) and 0.53 mm (SD: 0.25). Both repeatability and intersystem differences were within the self-reported 1 mm. The workflow was considered easy and effective, emphasizing the potential of this approach within a workflow to obtain patient specific splint.

Understanding Error Patterns: An Analysis of Alignment Errors in Rigid 3D Body Scans

Three-dimensional body scanners are attracting increasing interest in various application areas. To evaluate their accuracy, their 3D point clouds must be compared to a reference system by using a reference object. Since different scanning systems use different coordinate systems, an alignment is required for their evaluation. However, this process can result in translational and rotational misalignment. To understand the effects of alignment errors on the accuracy of measured circumferences of the human lower body, such misalignment is simulated in this paper and the resulting characteristic error patterns are analyzed. The results show that the total error consists of two components, namely translational and tilt. Linear correlations were found between the translational error (R2 = 0.90, … 0.97) and the change in circumferences as well as between the tilt error (R2 = 0.55, … 0.78) and the change in the body's mean outline. Finally, by systematic analysis of the error patterns, recommendations were derived and applied to 3D body scans of human subjects resulting in a reduction of error by 67% and 84%.

Reliability of a human pose tracking algorithm for measuring upper limb joints: comparison with photography-based goniometry

BACKGROUND

Range of motion (ROM) measurements are essential for diagnosing and evaluating upper extremity conditions. Clinical goniometry is the most commonly used methods but it is time-consuming and skill-demanding. Recent advances in human tracking algorithm suggest potential for automatic angle measuring from RGB images. It provides an attractive alternative for at-distance measuring. However, the reliability of this method has not been fully established. The purpose of this study is to evaluate if the results of algorithm are as reliable as human raters in upper limb movements.

METHODS

Thirty healthy young adults (20 males, 10 females) participated in this study. Participants were asked to performed a 6-motion task including movement of shoulder, elbow and wrist. Images of movements were captured by commercial digital cameras. Each movement was measured by a pose tracking algorithm (OpenPose) and compared with the surgeon-measurement results. The mean differences between the two measurements were compared. Pearson correlation coefficients were used to determine the relationship. Reliability was investigated by the intra-class correlation coefficients.

RESULTS

Comparing this algorithm-based method with manual measurement, the mean differences were less than 3 degrees in 5 motions (shoulder abduction: 0.51; shoulder elevation: 2.87; elbow flexion:0.38; elbow extension:0.65; wrist extension: 0.78) except wrist flexion. All the intra-class correlation coefficients were larger than 0.60. The Pearson coefficients also showed high correlations between the two measurements (p < 0.001).

CONCLUSIONS

Our results indicated that pose estimation is a reliable method to measure the shoulder and elbow angles, supporting RGB images for measuring joint ROM. Our results presented the possibility that patients can assess their ROM by photos taken by a digital camera.

TRIAL REGISTRATION

This study was registered in the Clinical Trials Center of The First Affiliated Hospital, Sun Yat-sen University (2021-387).