Comparative Analysis Between the Main 3D Scanning Techniques: Photogrammetry, Terrestrial Laser Scanner, and Structured Light Scanner in Religious Imagery: The Case of The Holy Christ of the Blood

In recent years, three-dimensional (3D) scanning has become the main tool for recording, documenting, and preserving cultural heritage in the long term. It has become the “document” most in demand today by historians, curators, and art restorers to carry out their work based on a “digital twin,” that is, a totally reliable and accurate model of the object in question. Thanks to 3D scanning, we can preserve reliable models in digital format of the real state of our heritage, some of which are currently destroyed. The first step is to digitize our heritage with the highest possible quality and precision. To do this, it will be necessary to identify the most appropriate technique. In this article, we will show some of the main digitization techniques currently used in sculpture heritage and the workflows associated with them to obtain high-quality models. Finally, a complete comparative analysis will be made to show their main advantages and disadvantages.

Co-registration Comparison of On-Scalp Magnetoencephalography and Magnetic Resonance Imaging

Magnetoencephalography (MEG) can non-invasively measure the electromagnetic activity of the brain. A new type of MEG, on-scalp MEG, has attracted the attention of researchers recently. Compared to the conventional SQUID-MEG, on-scalp MEG constructed with optically pumped magnetometers is wearable and has a high signal-to-noise ratio. While the co-registration between MEG and magnetic resonance imaging (MRI) significantly influences the source localization accuracy, co-registration error requires assessment, and quantification. Recent studies have evaluated the co-registration error of on-scalp MEG mainly based on the surface fit error or the repeatability error of different measurements, which do not reflect the true co-registration error. In this study, a three-dimensional-printed reference phantom was constructed to provide the ground truth of MEG sensor locations and orientations relative to MRI. The co-registration performances of commonly used three devices—electromagnetic digitization system, structured-light scanner, and laser scanner—were compared and quantified by the indices of final co-registration errors in the reference phantom and human experiments. Furthermore, the influence of the co-registration error on the performance of source localization was analyzed via simulations. The laser scanner had the best co-registration accuracy (rotation error of 0.23° and translation error of 0.76 mm based on the phantom experiment), whereas the structured-light scanner had the best cost performance. The results of this study provide recommendations and precautions for researchers regarding selecting and using an appropriate device for the co-registration of on-scalp MEG and MRI.

Three-dimensional ultrasound for knee osteophyte depiction: a comparative study to computed tomography

Purpose Osteophytes are common radiographic markers of osteoarthritis. However, they are not accurately depicted using conventional imaging, thus hampering surgical interventions that rely on pre-operative images. Studies have shown that ultrasound (US) is promising at detecting osteophytes and monitoring the progression of osteoarthritis. Furthermore, three-dimensional (3D) ultrasound reconstructions may offer a means to quantify osteophytes. The purpose of this study was to compare the accuracy of osteophyte depiction in the knee joint between 3D US and conventional computed tomography (CT). Methods Eleven human cadaveric knees were pre-screened for the presence of osteophytes. Three osteoarthritic knees were selected, and then, 3D US and CT images were obtained, segmented, and digitally reconstructed in 3D. After dissection, high-resolution structured light scanner (SLS) images of the joint surfaces were obtained. Surface matching and root mean square (RMS) error analyses of surface distances were performed to assess the accuracy of each modality in capturing osteophytes. The RMS errors were compared between 3D US, CT and SLS models. Results Average RMS error comparisons for 3D US versus SLS and CT versus SLS models were 0.87 mm ± 0.33 mm (average ± standard deviation) and 0.95 mm ± 0.32 mm, respectively. No statistical difference was found between 3D US and CT. Comparative observations of imaging modalities suggested that 3D US better depicted osteophytes with cartilage and fibrocartilage tissue characteristics compared to CT. Conclusion Using 3D US can improve the depiction of osteophytes with a cartilaginous portion compared to CT. It can also provide useful information about the presence and extent of osteophytes. Whilst algorithm improvements for automatic segmentation and registration of US are needed to provide a more robust investigation of osteophyte depiction accuracy, this investigation puts forward the potential application for 3D US in routine diagnostic evaluations and pre-operative planning of osteoarthritis.

Three-Dimensional Reproducibility of the Soft Tissue Landmarks Taken by Structured-Light Facial Scanner in Accordance with the Head Position Change

The aim of this study was to evaluate the three-dimensional reproducibility of the structured-light facial scanner according to the head position change. A mannequin head was used and angle of the mannequin’s axis-orbital plane to the true horizontal plane was adjusted to +10, +5, 0, −5, and −10°. Facial scanning was conducted 30 times, respectively, and 150 3D images were obtained. Reoriented landmarks of each group were compared and analyzed. Reproducibility decreased as the distance from the facial center increased. Additionally, the landmarks below showed lower reproducibility and higher dispersion than landmarks above. These differences occurred mainly in the anteroposterior direction as opposed to other directions. Positive inclination of the head position showed superior reproducibility compared to a negative inclination. This study showed that reproducibility of a structured-light scanner could be varied depending on the head position. Inaccuracies of landmarks in the anteroposterior direction are greater than in other directions. This means that evaluations of the profile using a structured-light scanner should be made carefully. Therefore, the proper head position should be set to ensure the accuracy of the image.

Shedding light on pre-Columbian crania collections through state-of-the-art 3D scanning techniques

<p class="VARAbstract">During the 19^th and 20^th centuries, numerous museums, scientific societies, and royal academies were founded in Europe and America. In this scenario, the Anthropological Museum Montané was founded in Havana, Cuba. Its collection has grown over the years, thanks to researchers, antiquarians, and amateurs. Since its foundation, the Museum Montané has become an essential institution for anthropological and archaeological research in the region. Nowadays, the Museum Montané, like other museums in developing countries, faces a challenge in the introduction of state-of-the-art technologies to digitizing exhibits and the creation of innovative projects to attract visitors. The current possibilities of virtualization of cultural heritage using digital technologies have a favorable impact on the preservation, access, and management of museum collections. The use of three-dimensional (3D) models fosters engagement with visitors, stimulates new forms of learning, and revalorizes the exhibits. In the current study, we use a hand-held structured light scanner to create 3D reality-based models of pre-Columbian crania from the Caribbean and South American collection of the Anthropological Museum Montané. The resulting 3D models were used for producing 3D printing replicas and animated videos. The 3D resources derived will encourage new knowledge through research, and provide broader access to these pre-Columbian crania collection through learning and outreach activities. The significance of digitizing these specimens goes beyond the creation of 3D models. It means protecting these fragile and valuable collections for future generations. The methodology and results reported here can be used in other museums with similar collections to digitally document, study, protect, and disseminate the archaeological heritage. Going forward, we seek to continue exploring the application of novel methods and digital techniques to the study of the pre-Columbian crania collections in Latin American and the Caribbean area.</p><p class="VARAbstractHeader">Highlights:</p><ul><li><p>A hand-held structured light scanner was used to acquire 3D reality-based models of pre-Columbian crania. The 3D models resulting were used for 3D printing replicas and 3D animations.</p></li><li><p>This study provides unprecedented 3D reconstructions of pre-Columbian crania in the Caribbean area, and new 3D reconstructions of artificially deformed crania from South America.</p></li><li><p>The 3D resources created will encourage new knowledge through research, and provide broader access to these pre-Columbian crania collection through learning and outreach activities.</p></li></ul>

3D Scanning of Semitransparent Amber with and without Inclusions

This paper is concerned with making 3D scans of semitransparent ambers with and without inclusions. The paper presents results of using a variety of devices applied for this purpose. Equipment used in the experiments includes a 3D laser scanner, a structured light scanner, a stereo camera, a camera array and a tomograph. The main object used in the experiment was an amber with a fossil of a lizard. The paper shows possibilities of acquiring the 3D structure of fossils embedded in semitransparent material which interfere with the measurement performed by 3D scanning equipment. Moreover, the paper shows the application of results of 3D scanning as the 3D scan of a lizard was reconstructed in a virtual reality cave making it possible to visualize in detail its shape and texture

Comparative Analysis of Object Digitization Techniques Applied to the Characterization of Deformed Materials in Ballistic Tests

Several three-dimensional scanning methods have been developed and improved over the past 40 years. The peculiarities of each technique, associated with the computational advances of the period, allowed the increasing application and diffusion of the technology in several sectors, among them those related to metrology in ballistics and the testing of protective materials. The specific goal of such ballistic tests is to estimate the depth of indentation caused by projectiles. In particular, this study presents a comparative analysis between two three-dimensional optical scanning methods, taking into account the same object of interest. The comparative analysis was based on reference planes detected by Random Sample Consensus methodology in each cloud. By comparing the results of the different techniques, it was found for this case that three-dimensional reconstruction by stereo images estimated values closer to the real ones in comparison to those estimated by the structured light scanner, mainly due to the fact that, for three-dimensional reconstruction, the image acquisition was conducted statically.

DENSE 3D OBJECT RECONSTRUCTION USING STRUCTURED-LIGHT SCANNER AND DEEP LEARNING

Structured light scanners are intensively exploited in various applications such as non-destructive quality control at an assembly line, optical metrology, and cultural heritage documentation. While more than 20 companies develop commercially available structured light scanners, structured light technology accuracy has limitations for fast systems. Model surface discrepancies often present if the texture of the object has severe changes in brightness or reflective properties of its texture. The primary source of such discrepancies is errors in the stereo matching caused by complex surface texture. These errors result in ridge-like structures on the surface of the reconstructed 3D model. This paper is focused on the development of a deep neural network LineMatchGAN for error reduction in 3D models produced by a structured light scanner. We use the pix2pix model as a starting point for our research. The aim of our LineMatchGAN is a refinement of the rough optical flow A and generation of an error-free optical flow B̂. We collected a dataset (which we term ZebraScan) consisting of 500 samples to train our LineMatchGAN model. Each sample includes image sequences (Sl, Sr), ground-truth optical flow B and a ground-truth 3D model. We evaluate our LineMatchGAN on a test split of our ZebraScan dataset that includes 50 samples. The evaluation proves that our LineMatchGAN improves the stereo matching accuracy (optical flow end point error, EPE) from 0.05 pixels to 0.01 pixels.