3D scanning

Nowadays the interest for improving methodologies to design customized external devices for the neck has considerably grown, considered that neck pathologies are widespread among the population. Their design for additive manufacturing starts by acquiring the body's part and, in order to achieve a satisfactory end result, the support of accurate reconstructed models from fast scans is relevant. At this aim, the availability of an average or statistical model could be potentially useful for reducing acquisition time and for upgrading low-resolution scans. This paper focuses on the application of a methodology for the creation of an average model of human neck. The method required the use of a set of scans, acquired by means of a structured light scanner, from which an accurate reconstruction of the neck surface was obtained. A number of healthy subjects of both genders was considered and the digital neck surfaces were used for creating an average digital model for males and for females. The methodology developed was based on mesh morphing and was applied to the sample considered with satisfactory results. The procedure is also suitable for the development of statistical models of the neck, that will cover future research

Keywords: Acquisition , Mesh morphing , Neck , Reverse Engineering

Survey missions in the underwater environment are key activities in several application fields, but the physical properties of such a harsh environment make it challenging for both navigation and data collection. In particular, in the field of underwater photogrammetry, optical sensors are mainly installed on remotely operated vehicles (ROVs). The maneuvering is performed remotely by expert pilots who can only rely on bidimensional visual feedback from one or more camera streams. Additional navigation data can aid pilots in assessing if the mission meets the requirements while undergoing it. To this end, the paper presents a SLAM-based solution that can be used to compute parameters in support of ROV pilots during photogrammetric surveys, when a stereo-camera is equipped. In order to assess the performance of the proposed solution, different tests were conducted. These tests involved comparing the parameters derived from SLAM with the data computed by the navigation system of a professional-grade ROV. The focus of this comparison was on three key parameters: position, velocity, and distance from the target.

Keywords: Multi-camera System , Underwater 3D Reconstruction , Underwater Photogrammetry , Underwater SLAM , Underwater Survey

Aim: The objective of this research has been to apply a specific simulation to a patient to assess the biomechanical consequences of rotating an upper canine tooth through different attachment–aligner configurations and to predict the most efficient design using a three-dimensional finite element model of a full maxillary arch of a specific patient. Materials and methods: This was obtained by combining Cone-Beam Computed Tomography (CBCT) with the aim of reconstructing tooth roots and bone tissues, and Surface Structured-Light Scanning for creating digital tooth crown models from the patient's impressions. This model was imported into the finite element solver (Ansys® 17). Three different attachment–aligner combinations were created through the exploitation of computer-aided design (CAD) procedures, i.e., without attachments, with a couple of attachments and with an attachment and a pressure point. For each simulation, the resulting force–moment (MF) system applied by the aligner to the target tooth, as well as the tooth displacement and rotation, was computed using a workstation based on Intel Xeon CPU E3-1245 v3@3.40 GHz and 16 GB RAM. Simulations reported that by adding the pressure point and the attachment to the standard aligner the amount of Moment z (Mz) delivered to the tooth increased almost two times. Results and conclusions: The maximum tooth displacement (0.85 mm) was obtained with the attachment and pressure point aligner, while the lowest (0.058 mm) was obtained with use of a couple of attachments. Both the attachment and the pressure point have the potential to enhance the appliance's effectiveness. Particularly, the pressure point showed a higher influence on the load absolute value. The method applied in the present study should be used to retrieve the best design configuration for each patient and specific tooth movement

Keywords: aligners , digital workflow , finite element analysis , malocclusion , orthodontic movement , three-dimensional diagnosis and analysis , three-dimensional tooth movement

3D printed patient-specific hand orthoses can improve the efficiency of the treatment and the comfort of the patient, but since each customized orthosis is a virtually unique device, it is difficult to assess their mechanical response in the design phase, both experimentally and numerically. The Finite Element Method (FEM) could be used to predict the deformation of the orthosis under predetermined loads, but patient-specific models including interaction with the hand are still lacking. In the present work we present a computational model in which, starting from the scan data of the hand used to manufacture the orthosis, a FEM model of the hand is generated, including a skeletal structure. Hand bones positions and dimensions can be defined basing on simple anatomical measurements or literature data and the stiffness of the joints can be tuned in relation to patient pathology. The remaining hand volume consists of a soft tissue region, mimicking the non-linear mechanical behaviour of skin and muscles. Results show that both functional and structural indexes can be analyzed, such as contact pressures, stress state or the compliance of the orthosis, providing useful information for the design of custom devices. By using mesh deformation algorithms, the scan data could be used to generate different orthosis designs in target positions defined by the therapist and, taking advantage of a parametric model under development, the skeletal structure could be adapted correspondingly, providing an innovative pathway to investigate the response of the orthosis during the whole rehabilitation.

Keywords: 3D Printing , FEM , Hand Orthosys

Objectives: Nowadays, a wide variety of software for 3D reconstruction from CT scans is available; they differ for costs, capabilities, a priori knowledge, and, it is not trivial to identify the most suitable one for specific purposes. The article is aimed to provide some more information, having set up various metrics for the evaluation of different software's performance. Methods: Metrics include software usability, segmentation quality, geometric accuracy, mesh properties and Dice Similarity Coefficient (DSC). Five different software have been considered (Mimics, D2P, Blue Sky Plan, Relu, and 3D Slicer) and tested on four cases; the mandibular bone was used as a benchmark. Results: Relu software, being based on AI, was able to solve some very intricate geometry and proved to have a very good usability. On the other side, the time required for segmentation was significantly higher than other software (reaching over twice the time required by Mimics). Geometric distances between nodes position calculated by different software usually kept below 2.5 mm, reaching 3.1 mm in some very critical area; 75th percentile q75 is generally less than 0.5 mm, with a maximum of 1.11 mm. Dealing with consistency among software, the maximum DSC value was observed between Mimics and Slicer, D2P and Mimics, and D2P and Slicer, reaching 0.96. Significance: This work has demonstrated how mandible segmentation performance among software was generally very good. Nonetheless, differences in geometric accuracy, usability, costs and times required can be significant so that information here provided can be useful to perform an informed choice.

Keywords: 3D reconstruction , CT scans , DSC , Geometric accuracy , Mandible , Segmentation , Usability

This work is aimed to set-up a methodology for foot shape prediction at different flexion angles, overcoming limitations encountered when different poses are required but a limited set of acquisitions can be performed. The basic idea was to identify a fitting law able to interpolate positions of foot anatomical landmarks, and then use this information to guide the deformation of an average foot shape. First of all, mesh correspondence between foot geometries was accomplished by an established procedure based on mesh morphing. Then Procrustes analysis was applied to the dataset to remove rigid motions and estimate the average shape. Two interpolation laws (linear and quadratic) were investigated and the best one in terms of prediction of 3D landmarks' coordinates was identified. Finally, shape geometries at any flexion angle were predicted performing a second mesh morphing guided by interpolated landmarks' displacements from the average shape. These analyses proved that a limited number of interpolation angles provides a prediction accuracy comparable to that obtained using all the angles available in the dataset. Moreover, predicted shapes have been compared to the actual scans in terms of root mean square error between corresponding nodes, obtaining a mean value of 4.03 ± 1.39 mm, in accordance with data reported in literature.

Keywords: Accurate geometric reconstruction , Foot model , Real-time acquisition , Statistical deformation model , Statistical shape model

Current technological developments in the field of sensor capture and additive manufacturing (AM) from computer models have led to innovative solutions for a 3D reconstruction of anatomical parts of the human body in real time, enabling interesting applications in the medical field and especially in orthopedics. The following work proposes the use of new technologies applied to tele-rehabilitation so that the patient can benefit from remote rehabilitation services. The wrist motion performed by the physical therapist was to be compared with the wrist motion of the patient undergoing rehabilitation, so as to obtain a proper analysis on the treatment to be followed, the expected timing and the recovery goals. Future applications could involve the use of the proposed system within hospitals and rehabilitation centers in order to support health care providers, improve patient care and quality of life, and contribute to the innovation of new approaches for medical assessment.

Keywords: Acquisition , Flexion-Extension , Radial-Ulnar deviation , Rehabilitation , Wrist

Reduction of aerodynamic drag is a crucial aspect of cycling. Currently, to optimize aerodynamics, athletes rely on wind tunnel tests or CFD simulations. Despite the undeniable advantage of the latter in terms of cost and time effort, they still require validation through wind tunnel measurements. This paper introduces a novel workflow that aims to streamline and accelerate the aerodynamic analysis process for cycling. The proposed workflow focuses on utilizing a full-sized mannequin and integrates CFD simulations, wind tunnel validation, 3D scanning, and rigging animation techniques. The animation technique involves the creation of a virtual skeleton that allows the scanned model to be posed in any desired position, eliminating the need for physical adjustments and repetitive wind tunnel testing. To showcase the time-saving advantages of this approach, a steady CFD analysis is conducted to compare six different configurations obtained using the rigged model, in terms of drag areas, velocity streamlines, and pressure coefficient distribution. The obtained data trends closely align with previous similar studies in the literature and the results from the simulation have been compared with wind tunnel test measurements. Additionally, future adjustments to the position or equipment can be easily made using the virtual rigging model. By integrating virtual techniques with CFD simulations and wind tunnel validation, the proposed workflow enables rapid evaluation of aerodynamic performance in a more efficient and cost-effective manner.

Keywords: CFD , Cyclist , Rigging Animation

For the more than 100 years forensic firearm identification has been conducted by examining physical evidence under the optical comparison microscope. Nowadays, 3D technology offers advanced and powerful tools that deserve to be considered to evaluate a new and different solution for processing ballistic data. The method proposed in this work is based on the processing of the 3D point clouds of the cartridge case back. It starts with the transformation of the point clouds of the bottom of the cartridge case into a 64-bit greyscale image. The second step is to use a polar derivation technique for exploiting the polar characteristics of the features impressed on the cartridge and also to overcome the problem of the initial orientation of the cartridge. The dataset used for the experimental part was made by Messina Carabinieri Scientific Investigation Department (Italy) and it contains point clouds of several cartridge cases acquired with an Automated Ballistic Identification System (ABIS). After the pre-processing, the method has been tested with SIFT to verify the invariance on the feature extracted. Although not yet ready for forensic applications, the method appears to be promising and innovative to be applied in the common pattern recognition process in this field.

Keywords: Ballistics , Cartridge Cases , Firearm Identification , Forensics , Point Clouds

The present work proposes the use of point clouds differential entropy as a new method for reverse engineering quality assessment. This quality assessment can be used to measure the shape deviation of objects made with additive manufacturing or CNC techniques. The quality of the execution is intended as a measure of the deviation of the geometry of the obtained object compared to the original CAD model. The method exploits the quality index of the CorAl method. The advantages of CorAl are several, among them the use of a unique index of comparison, no problem of commutativity of the comparison, noise immunity, low influence of the presence of holes and of the point cloud densities. It is possible to plot quality maps showing the areas with the greatest deviation. In experiments, objects obtained by additive manufacturing with different print qualities are tested. The robustness of the method is also demonstrated. The quality index evaluated for each object, as defined in the CorAl method, turns out to be gradually closer to 0 as the quality of the piece's construction increases.

Keywords: Deviation Analysis , Differential Entropy , Point Clouds , Quality Assessment

Over the last few years, significant interest has been addressed in developing computer-based methods to document and analyze fragments of ceramics sherds in archaeology. This is because traditional manual processes do not allow for an objective, repeatable, and reproducible analysis of the large quantities of material needed to fully understand and explain human practices in various cultural contexts, such as the economy, daily life, and the material expression of religious beliefs. In that context, this paper proposes a fully digital methodology resulting from the constitution of an international research group coming from different scientific backgrounds: archaeologists with specific skills and experience in fast 3D geometry acquisition methods and researchers who developed and published the only available computer-based process for recognizing the geometric and morphological sherds features analyzed by archaeologists. The proposed methodology consists of two main parts: 1. 3D acquisition of sherds with the construction of the discrete 3D manifold model based on the Structure for Motion technologies; 2. recognition, segmentation, and dimensional characterization of morphological and geometrical features based on the codification and algorithmic implementation of the knowledge used by the archeologists in the traditional method. The method was applied to analyze a set of 133 sherds excavated at Tell el-Burak (Lebanon) to obtain, through the analysis of the namely Phoenician carinated-shoulder amphorae, new insights into the economic organization of the Phoenician homeland. The method demonstrated the potential for objectively, repeatedly, and reproducibly analyzing large quantities of sherds. Furthermore, it allowed studying sherds by generating new high-level knowledge from those acquired from 3D models; in particular, this paper introduces new morphological features that help the archaeologist classify fragments from an analysis of the rim's shape.

Keywords: 3D archeology , Automatic feature recognition , Hierarchical rims clusterization , Phoenician amphorae , Pottery , Structure from motion

The alignment of large datasets associated with 3D reconstructions is still an open issue in the scientific community. Among the several strategies available in the literature, some are based on using geometrical features. In this paper, the Authors have investigated the reliability of associating ideal planes with non-ideal roof features, which may be used to realign 3D terrestrial reconstructions. The obtained results underline a deep influence from noise, which affects the non-ideal roof feature and ideal plane association, and the necessity to define additional experiments to confirm the robustness of the solution.

Keywords: feature-based alignment , marker-less alignment , non-ideal feature approximation , terrestrial point-cloud

The paper proposes a new recognition rule to automatically identify the spine line by detecting vertebral apophyses from discrete models of human backs collected by 3D scanning. Unlike previous 3D optical approaches, the process described here aims to directly detect spinal apophyses, following the posturologist's method. These anatomical landmarks are identified not as areas of the back surface with specific shapes, but by searching for appropriate local shape perturbations. Except for vertebral prominences that are convex regions, spinal apophyses are generally unrelated to specific surface shapes. The rule has been tested on several human backs. For each, an experienced operator identified the spinal apophyses from palpation and indicated their position by applying an adhesive marker on the back surface. These positions are used as a reference to compare the vertebral apophyses automatically localized by the methodology proposed here. The experimental results show that the rule discriminates well even blurred vertebral prominences.

Keywords: 3D optical methods , Local shape analysis , Shape index , Spinal apophyses recognition , Spine line

Background: In recent years, the treatment of wrist fractures has been the focus of numerous studies, particularly in the development of casts modeled on the patient's anatomy using additive manufacturing techniques. A 3D printed cast offers several advantages over traditional treatment methods, including washability, lightness, and ventilation. Objective: This work introduces an automatic procedure for designing patient-specific wrist orthoses from a 3D scan of the arm using open-source mesh-processing libraries. Methods: The procedure consists of seven steps that generate a customized orthosis model. Due to the absence of a single library capable of completing the entire modeling process, we defined the best execution strategy for each step and established a communication flow between the various blocks. Results: The resulting orthosis comprises two halves, secured by three appropriately positioned bands and perforated with ventilation holes. The modeling procedure takes approximately 5 min to complete and was evaluated on 20 scans of arms of different shapes and sizes. The process proved to be fast, reliable, and suitable for direct use by medical personnel. Conclusions: The developed automatic procedure for designing patient-specific wrist orthoses is efficient and effective, facilitating the use of 3D printed casts in medical practice.

Keywords: 3D modelling , 3D printed orthosis , Personalized medicine , Reverse engineering , Wrist orthosis

In mechanical design, tolerance stack-up has a fundamental role to ensure mechanical coupling among assembly components. To avoid interferences, gaps between connected parts are introduced since the design phase, to compensate for possible dimensional variations. The present study aims to assess clearances in the Volkswagen Crafter chassis, by comparing the CAD model to the 3D reconstruction of the real van, obtained by means of 3D scanning. This activity has been carried out within SMART AMBULANCE project (POR FESR Toscana call), which has as its goal the realization of an advanced ambulance by implying smart technologies. Clearance analysis was performed before proceeding with the design of the interior setup of the ambulance medical compartment, since even small deviations may compromise the assembly of the covering panels. The analysis was useful not only to evaluate deviations between ideal and real geometry, but also to identify the locations of the gaps.

Keywords: 3D scanning , CAD model , Deviation Analysis , Reverse Engineering , Tolerance Stack-ups

The treatment of burn scars is a hotly debated and delicate subject since ineffective therapy can significantly lower quality of life. Ideally, medical evaluation should leverage objective assessments of progress over time to provide an adequate assessment of scar health and related treatment. In contrast, common clinical practice involves medical examination that rely on subjective assessment scales such as Vancouver Scar Scale and the Patient and Observer Scar Assessment Scale. Recently, extraction of objective parameters for the investigation of scar surface were studied by objectively analyzing the surface topography and extracting scar roughness through a transposition of standard mechanical surface evaluation methods, which are based on ISO 4287 and ISO 4288, to the clinical field. The most advanced methods analyze the scar roughness globally and after subdividing it in sub-patches of pre-fixed dimension. In both cases, it is not considered that the scar may be located in non-planar portions of the body, therefore, roughness values are dependent from the principal roughness evaluation direction. In the present work these shortfalls are overcome using a systematic procedure to subdivide the patches in a consistent manner and analyze smaller portions of the surface providing a roughness value independent of the filtering direction.

Keywords: 3D scar model , Automatic assessment , Burn scar , Surface roughness

In remanufacturing, Reverse Engineering (RE) tools and techniques could become essential in the rapid creation of digital 3D models of existing components, especially when drawings are no longer available. These models can be used to investigate potential remanufacturable parts, identify damages or defects and assist in the decision-making process for as-is rebuilding or redesigning of the part to improve performance. In this context, Additive Manufacturing (AM) technology is particularly well suited due to its capability to rapidly produce parts with minimal geometry constraints and at relatively low cost. This study proposes a methodological procedure based on the combined use of RE-AM to facilitate the remanufacturing decision-making process for better part performance and strategy. Moreover, through the use of Machine Learning (ML) algorithms, damages can be automatically and objectively identified and quantified. An application case is used to demonstrate the effectiveness of the proposed approach.

Keywords: Additive manufacturing , Machine learning , Methodological procedure , Remanufacturing , Reverse engineering

This paper describes a robust design approach to optimize the design of smart shorts for muscle activity analysis. A practical application related to electromyographic shorts for monitoring six main thigh muscles is shown. Starting from a 2D digital model of a pattern block related to the shorts, a robust design approach is applied to optimize the design of textile electrodes for surface electromyography analysis in terms of size (i.e., diameter), and location (i.e., inter-electrode distance). The aim is to reduce the sensitiveness to noise factors (i.e., skin lubrication condition, anthropometric variability and gesture type) guaranteeing the best performance in terms of Signal Noise Ratio. The experimental campaign related to football activities allows the practical application of the proposed approach for the design of smart shorts for football. The results allow to define the optimal configurations for the six muscles of interest. This work might pave the way for the development of tailored smart garments for electromyography analysis.

Keywords: electromyographic system , human body scanning , robust design , wearable sensors

Additive Manufacturing has transformed modern manufacturing with its well-known advantages. However, shrinkage remains a critical challenge, causing dimensional inaccuracies that should be properly compensated to assure geometric fidelity. This study aims to assess the reliability of a Reverse Engineering (RE) technique for dimensional compensation. A gauge-based measurement approach has been used to validate the RE method. Results confirm that the RE method is promising, while highlighting the intrinsic errors of the RE technique, and suggesting ways to evaluate and prevent them.

Keywords: additive manufacturing , design for additive manufacturing , reverse engineering , scale factor , shrinkage compensation

A bi-level analysis of computed tomography (CT) images of malignant pleural mesothelioma (MPM) is presented in this paper, starting with a deep learning-based system for classification, followed by a three-dimensional (3D) reconstruction method. MPM is a highly aggressive cancer caused by asbestos exposure, and accurate diagnosis and determination of the tumor's volume are crucial for effective treatment. The proposed system employs a bi-level approach, utilizing machine learning and deep learning techniques to classify CT lung images and subsequently calculate the tumor's volume. The study addresses challenges related to deep neural networks, such as the requirement for large and diverse datasets, hyperparameter optimization, and potential data bias. To evaluate performance, two convolutional neural network (CNN) architectures, Inception-v3 and ResNet-50, were compared in terms of their features and performance. Based on CT images, the second stage incorporates 3D volume reconstruction. The process is carried out by cropping, registering, filtering, and segmenting images. This study demonstrated the efficacy of the developed system by combining CNN optimizations with 3D image reconstruction. It is intended to improve the accuracy of MPM diagnosis and to assist in the determination of chemotherapy doses, both of which may result in improved outcomes for patients.

Keywords: 3D reconstruction , CNN , CT imaging , malignant pleural mesothelioma