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The aim of this work was to assess the accuracy, repeatability, and reproducibility of a hand-held, structured-light 3D scanner (EINScan Pro 2X Plus with High Definition Prime Pack, SHINING 3D Tech. Co., Ltd., Hangzhou, China), to support its potential use in multi-site settings on lower limb prosthetics. Four limb models with different shapes were fabricated and scanned with a metrological 3D scanner (EINScan Laser FreeScan 5X, SHINING 3D Tech. Co., Ltd., Hangzhou, China) by a professional operator (OP0). Limb models were then mailed to three sites where two operators (OP1, OP2) scanned them using their own structured-light 3D scanner (same model). OP1 scanned limb models twice (OP1-A, OP1-B). OP0, OP1-A, and OP2 scans were compared for accuracy, OP1-A and OP1-B for repeatability, and OP1-A and OP2 for reproducibility. Among all comparisons, the mean radial error was <0.25 mm, mean angular error was <4°, and root mean square error of the radial distance was <1 mm. Moreover, limits of agreement were <3.5% for perimeters and volumes. By comparing these results with respect to clinically-relevant thresholds and to the literature available on other 3D scanners, we conclude that the EINScan Pro 2X Plus 3D Scanner with High Definition Prime Pack has good accuracy, repeatability, and reproducibility, supporting its use in multi-site settings.

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.

The effect of temperature on three-dimensional (3D) structured light scanners is a very complex issue that, under some conditions, can lead to significant deterioration of performed measurements. In this paper, we present the results of several studies concerning the effect of temperature on the mechanical base of 3D-structured light scanners. We also propose a software compensation method suitable for implementation in any existing scanner. The most significant advantage of the described method is the fact that it does not require any specialized artifact or any additional equipment, nor access to the thermal chamber. It uses a simulation of mechanical base thermal deformations and a virtual 3D measurement environment that allows for conducting virtual measurements. The results from the verification experiments show that the developed method can extend the range of temperatures in which 3D-structured light scanners can perform valid measurements by more than six-fold.

Purpose Body surface area is a physiological quantity relevant for many medical applications. In clinical practice, it is determined by empirical formulae. 3D laser-based anthropometry provides an easy and effective way to measure body surface area but is not ubiquitously available. We used data from laser-based anthropometry from a population-based study to assess validity of published and commonly used empirical formulae. Methods We performed a large population-based study on adults collecting classical anthropometric measurements and 3D body surface assessments ( N  = 1435). We determined reliability of the 3D body surface assessment and validity of 18 different empirical formulae proposed in the literature. The performance of these formulae is studied in subsets of sex and BMI. Finally, improvements of parameter settings of formulae and adjustments for sex and BMI were considered. Results 3D body surface measurements show excellent intra- and inter-rater reliability of 0.998 (overall concordance correlation coefficient, OCCC was used as measure of agreement). Empirical formulae of Fujimoto and Watanabe, Shuter and Aslani and Sendroy and Cecchini performed best with excellent concordance with OCCC > 0.949 even in subgroups of sex and BMI. Re-parametrization of formulae and adjustment for sex and BMI slightly improved results. Conclusion In adults, 3D laser-based body surface assessment is a reliable alternative to estimation by empirical formulae. However, there are empirical formulae showing excellent results even in subgroups of sex and BMI with only little room for improvement.

The accuracy of 3D reconstructions of the craniomaxillofacial region using cone beam computed tomography (CBCT) is important for the morphological evaluation of specific anatomical structures. Moreover, an accurate segmentation process is fundamental for the physical reconstruction of the anatomy (3D printing) when a preliminary simulation of the therapy is required. In this regard, the objective of this study is to evaluate the accuracy of four different types of software for the semiautomatic segmentation of the mandibular jaw compared to manual segmentation, used as a gold standard. Twenty cone beam computed tomography (CBCT) with a manual approach (Mimics) and a semi-automatic approach (Invesalius, ITK-Snap, Dolphin 3D, Slicer 3D) were selected for the segmentation of the mandible in the present study. The accuracy of semi-automatic segmentation was evaluated: (1) by comparing the mandibular volumes obtained with semi-automatic 3D rendering and manual segmentation and (2) by deviation analysis between the two mandibular models. An analysis of variance (ANOVA) was used to evaluate differences in mandibular volumetric recordings and for a deviation analysis among the different software types used. Linear regression was also performed between manual and semi-automatic methods. No significant differences were found in the total volumes among the obtained 3D mandibular models (Mimics = 40.85 cm3, ITK-Snap = 40.81 cm3, Invesalius = 40.04 cm3, Dolphin 3D = 42.03 cm3, Slicer 3D = 40.58 cm3). High correlations were found between the semi-automatic segmentation and manual segmentation approach, with R coefficients ranging from 0,960 to 0,992. According to the deviation analysis, the mandibular models obtained with ITK-Snap showed the highest matching percentage (Tolerance A = 88.44%, Tolerance B = 97.30%), while those obtained with Dolphin 3D showed the lowest matching percentage (Tolerance A = 60.01%, Tolerance B = 87.76%) (p < 0.05). Colour-coded maps showed that the area of greatest mismatch between semi-automatic and manual segmentation was the condylar region and the region proximate to the dental roots. Despite the fact that the semi-automatic segmentation of the mandible showed, in general, high reliability and high correlation with the manual segmentation, caution should be taken when evaluating the morphological and dimensional characteristics of the condyles either on CBCT-derived digital models or physical models (3D printing).

Autonomous navigation of ground vehicles on natural environments requires looking for traversable terrain continuously. This paper develops traversability classifiers for the three-dimensional (3D) point clouds acquired by the mobile robot Andabata on non-slippery solid ground. To this end, different supervised learning techniques from the Python library Scikit-learn are employed. Training and validation are performed with synthetic 3D laser scans that were labelled point by point automatically with the robotic simulator Gazebo. Good prediction results are obtained for most of the developed classifiers, which have also been tested successfully on real 3D laser scans acquired by Andabata in motion.

The purpose of this study was to evaluate the accuracy of dental three-dimensional (3D) scanners according to the types of teeth. A computer-aided design (CAD) reference model (CRM) was obtained by scanning the reference typodont model using a high-precision industrial scanner (Solutionix C500, MEDIT). In addition, a CAD test model (CTM) was obtained using seven types of dental 3D scanners (desktop scanners (E1 and DOF Freedom HD) and intraoral scanners (CS3500, CS3600, Trios2, Trios3, and i500)). The 3D inspection software (Geomagic control X, 3DSystems) was used to segment the CRM according to the types of teeth and to superimpose the CTM based on the segmented teeth. The 3D accuracy of the scanner was then analyzed according to the types of teeth. One-way analysis of variance (ANOVA) was used to compare the differences according to the types of teeth in statistical analysis, and the Tukey HSD test was used for post hoc testing (α = 0.05). Both desktop and intraoral scanners showed significant differences in accuracy according to the types of teeth (P < 0.001), and the accuracy of intraoral scanners tended to get worse from anterior to posterior. Therefore, when scanning a complete arch using an intraoral scanner, the clinician should consider the tendency for the accuracy to decrease from anterior to posterior.

This article concerns the research of the HUBO full-body scanner, which includes the analysis and selection of the scanner’s geometrical parameters in order to obtain the highest possible accuracy of the reconstruction of a human figure. In the scanner version analyzed in this paper, smartphone cameras are used as sensors. In order to process the collected photos into a 3D model, the photogrammetry technique is applied. As part of the work, dependencies between the geometrical parameters of the scanner are derived, which allows to significantly reduce the number of degrees of freedom in the selection of its geometrical parameters. Based on these dependencies, a numerical analysis is carried out, as a result of which the initial values of the geometrical parameters are pre-selected and distribution of scanner cameras is visualized. As part of the experimental research, the influence of selected scanner parameters on the scanning accuracy is analyzed. For the experimental research, a specially prepared dummy was used instead of the participation of a real human, which allowed to ensure the constancy of the scanned object. The accuracy of the object reconstruction was assessed in relation to the reference 3D model obtained with a scanner of superior measurement uncertainty. On the basis of the conducted research, a method for the selection of the scanner’s geometrical parameters was finally verified, leading to the arrangement of cameras around a human, which guarantees high accuracy of the reconstruction. Additionally, to quantify the results, the quality rates were used, taking into account not only the obtained measurement uncertainty of the scanner, but also the processing time and the resulting efficiency.

This study demonstrates the development and application of a novel workflow for designing and fabricating orthoses, using a combination of 3D scanning and 3D printing technologies. The workflow is applied to a clinically relevant translational case study in a patient with a neurological disorder and complex clinical needs. All traditional and commercial approaches to helping the patient’s cervical instability and resulting ‘head-drop’ had previously failed, with associated progressive deterioration in the patient’s clinical state and posture. The workflow was developed to design and fabricate a bespoke device for this patient with no viable alternative therapy. The workflow was developed to generate 3D printable geometry from obtained 3D scan data. The workflow includes algorithms to relax geometry, distribute material efficiently and for variational cutting of orthosis padding material. The 3D patient scan was validated against actual measurements to ensure accuracy of measurements. A total of four prototypes were produced with each iteration being improved based on patient and clinical feedback. There was a progressive improvement in subjective feedback through each iteration at sites of discomfort and overall comfort score. There was a marked improvement in the patient’s posture with correction at the cervical and lumbar spine with the 3D-printed padded collar being worn for 4 hour periods. This study has implications for the rapid production of personalised orthoses which can help reduce patient waiting time, improve patient compliance, reduce pain and reduce further deterioration. The workflow could form the basis for an integrated process, whereby a single hospital visit results in a bespoke orthosis optimised and personalised for each patient.

When a limb suffers a fracture, rupture, or dislocation, it is traditionally immobilized with plaster. This may induce discomfort in the patient, as well as excessive itching and sweating, which creates the growth of bacteria, leading to an unhygienic environment and difficulty in keeping the injury clean during treatment. Furthermore, if the plaster remains for a long period, it may cause lesions in the joints and ligaments. To overcome all of these disadvantages, orthoses have emerged as important medical devices to help patients in rehabilitation, as well as for self-care of deficiencies in clinics and daily life. Traditionally, these devices are produced manually, which is a time-consuming and error-prone method. From another point of view, it is possible to use imageology (X-ray or computed tomography) to scan the human body; a process that may help orthoses manufacturing but which induces radiation to the patient. To overcome this great disadvantage, several types of 3D scanners, without any kind of radiation, have emerged. This article describes the use of various types of scanners capable of digitizing the human body to produce custom orthoses. Studies have shown that photogrammetry is the most used and most suitable 3D scanner for the acquisition of the human body in 3D. With this evolution of technology, it is possible to decrease the scanning time and it will be possible to introduce this technology into clinical environment.