Characterizing Low-cost Registration for Photographic Images to Computed Tomography.

Mapping information from photographic images to volumetric medical imaging scans is essential for linking spaces with physical environments, such as in image-guided surgery. Current methods of accurate photographic image to computed tomography (CT) image mapping can be computationally intensive and/or require specialized hardware. For general purpose 3-D mapping of bulk specimens in histological processing, a cost-effective solution is necessary. Here, we compare the integration of a commercial 3-D camera and cell phone imaging with a surface registration pipeline. Using surgical implants and chuck-eye steak as phantom tests, we obtain 3-D CT reconstruction and sets of photographic images from two sources: Canfield Imaging's H1 camera and an iPhone 14 Pro. We perform surface reconstruction from the photographic images using commercial tools and open-source code for Neural Radiance Fields (NeRF) respectively. We complete surface registration of the reconstructed surfaces with the iterative closest point (ICP) method. Manually placed landmarks were identified at three locations on each of the surfaces. Registration of the Canfield surfaces for three objects yields landmark distance errors of 1.747, 3.932, and 1.692 mm, while registration of the respective iPhone camera surfaces yields errors of 1.222, 2.061, and 5.155 mm. Photographic imaging of an organ sample prior to tissue sectioning provides a low-cost alternative to establish correspondence between histological samples and 3-D anatomical samples.

Integrated high-precision real scene 3D modeling of karst cave landscape based on laser scanning and photogrammetry.

In recent years, the application of real scene 3D technology has become widespread in urban planning and cultural heritage protection. However, there has been relatively little attention paid to the construction of real scene 3D models for special natural landscapes such as caves. Given the global distribution of karst topography and the large number of naturally developed caves with diverse types, unique landscape styles, and significant scientific value, this paper enriches the research in this field. By combining ground-based and aerial remote sensing techniques, and based on 3D laser scanning and photogrammetry, we have successfully constructed a real scene 3D model of the internal structure of a karst cave with a precision better than 4 cm. Utilizing Unmanned Aerial Vehicle (UAV) oblique photography, we established a real scene 3D model of the external karst landform with a precision better than 2 cm. We also integrated the internal and external 3D models of the cave, developing a new, complete, and high-precision method for constructing real scene 3D models of karst cave landscapes. Furthermore, we proposed a method for texture reproduction in the dark environment inside the caves, enhancing the reproduction and visual appeal of the real interior. The establishment of high-precision real scene 3D models can not only serve as an effective tool for scientific research on caves but also, as replicas of the real world, play a crucial role in public dissemination and education, thereby enhancing public understanding of cave geological landscapes.

3D modelling method and application to a digital campus by fusing point cloud data and image data.

Objective: The use of single-source data for real-world 3D modelling currently faces problems such as deformation, pulling and fuzzy texture at the bottom of buildings in some feature models because of the lack of images. Moreover, LIDAR generates a huge amount of data, and the massive raw data processing and point cloud parsing puts high demands on the hardware arithmetic and algorithms. Aiming at the deficiencies and defects of the two data sources of inclined photogrammetry and airborne laser point cloud in the construction of high-quality and high-precision city-level 3D models. Methods: this study uses a university library building as an example and proposes the main technical process and method of modelling after fusing the point cloud data acquired by inclined photogrammetry and 3D laser scanning technology. This is accomplished in the reconstruction stage of multi-source data fusion through data spatial alignment, coordinate system unification and data spatial integration. At the stage of multi-source data fusion and reconstruction, through data spatial alignment, coordinate system unification, point cloud coarse alignment and the iterative closest point (ICP) algorithm, a realistic 3D model of a building is constructed to verify the effectiveness of the modelling method. Results: The method can effectively improve the accuracy of the real-life 3D model, repair the deficiencies in the model and optimise the details of the model. It can also significantly improve the fineness of the tilt photography model and perfectly present the geometric and texture information of the building, making it a superior method for fine 3D reconstruction. Conclusion: This 3D reconstruction method of buildings, which integrates low-altitude inclined photogrammetry and airborne light detection and ranging (LiDAR), has high positional accuracy and can provide new methods and new ideas for the construction of digital campuses as well as for other engineering applications.

A Linear Regression Approach for Best Scanline Determination in the Object to Image Space Transformation Using Pushbroom Images.

The use of linear array pushbroom images presents a new challenge in photogrammetric applications when it comes to transforming object coordinates to image coordinates. To address this issue, the Best Scanline Search/Determination (BSS/BSD) field focuses on obtaining the Exterior Orientation Parameters (EOPs) of each individual scanline. Current solutions are often impractical for real-time tasks due to their high time requirements and complexities. This is because they are based on the Collinearity Equation (CE) in an iterative procedure for each ground point. This study aims to develop a novel BSD framework that does not need repetitive usage of the CE with a lower computational complexity. The Linear Regression Model (LRM) forms the basis of the proposed BSD approach and uses Simulated Control Points (SCOPs) and Simulated Check Points (SCPs). The proposed method is comprised of two main steps: the training phase and the test phase. The SCOPs are used to calculate the unknown parameters of the LR model during the training phase. Then, the SCPs are used to evaluate the accuracy and execution time of the method through the test phase. The evaluation of the proposed method was conducted using ten various pushbroom images, 5 million SCPs, and a limited number of SCOPs. The Root Mean Square Error (RMSE) was found to be in the order of ten to the power of negative nine (pixel), indicating very high accuracy. Furthermore, the proposed approach is more robust than the previous well-known BSS/BSD methods when handling various pushbroom images, making it suitable for practical and real-time applications due to its high speed, which only requires 2-3 s of time.

Optical Target Projector: Principle of Functioning and Basic Performance Test.

Faced with measurement conditions such as high-temperature forging, strict prohibition of surface contamination, and toxic environments, using the projection point of an optical target projector (referred to as an "optical projector") as a photogrammetric target has become a necessary method of high-precision industrial photogrammetry. In connection with the current industrial demand, we have analyzed the principles of optical projectors and introduced their optical characteristics and advantages in the field of industrial photogrammetry. On this basis, a series of tests such as brightness, roundness, and so on were conducted to determine the basic properties of the optical projector. A set of performance test methods including inner coincidence accuracy and outer coincidence accuracy were proposed; the tests included industrial photogrammetry system measurement repeatability, surface measurement precision, and a comparison test with laser tracker. The test conditions used optical projection points as the photogrammetry targets. The test results showed that the coordinate measurement repeatability of the industrial photogrammetry system is 0.010 mm, and the surface measurement precision is 0.007 mm under the condition of a single optical projector station, with little difference between the results under the condition of pasting retro-reflective targets. In the process of the comparison test with laser tracker, the image quality of the black measurement object obtained is obviously inferior to other surfaces, so the analysis of the point projector is greatly affected by the color of the measured object and other conditions, which provides a reference for the measurement object and application range of the industrial photogrammetric system based on optical targets. The results demonstrate the applicability and reliability of using the optical projection point of an optical projector as target points for photogrammetry.

Comparative 3D Analysis of Lip Rejuvenation: Investigating Effects Before and After Soft-Tissue Filler Compared with Controls.

BACKGROUND: The aim of this study was to evaluate changes in lip metrics before and after facial rejuvenation treatment with hyaluronic acid-based fillers and to compare them with those of a control group using stereophotogrammetry (3D). METHODOLOGY: This study included 63 Caucasian women divided into Group C (<30 years, n=30) and Group H (>30 years, n=33), which was further divided into before (HT0) and after (HT1) lip augmentation with hyaluronic acid (HA). Eleven anthropometric landmarks were identified for linear, angular, and surface area measurements. Three photos were captured in Group C, while Group H had photos taken at T0 and T1. Statistical analysis was conducted using the Shapiro-Wilk test to evaluate normality, the Kruskal-Wallis test and one-way ANOVA. Tukey's post hoc and pairwise comparison tests were performed to analyze differences between variables (P value < 0.05). RESULTS: There were significant differences between lip width (ChR-ChL) and philtrum width (CphR-CphL) (P<.001). The total heights of the upper (Ls-Li) and lower vermilion lips (Sto-Li) increased, and the heights of the upper (Sn-Ls) and lower (Li-Sl) cutaneous lips decreased. The angles related to the philtrum (ChR-CphR-Ls, P<.001; ChL-CphL-Ls, P<.001) and nasolabial angle (Prn-Sn-Ls) (P<.001) exhibited significant differences. The surface areas of the upper, lower, and total vermilion lip showed significant differences (P<.001). Tukey's test indicated no significant differences in surface area after lip augmentation between the HT1 and C groups. CONCLUSION: Analysis of lip morphology after a filler procedure revealed a reversal of age-related changes, with increases in vermilion lip height and surface area comparable to those of younger individuals. LEVEL OF EVIDENCE II: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors   www.springer.com/00266 .

Using 3D facial information to predict malnutrition and consequent complications.

BACKGROUND: Phase angle (PhA) correlates with body composition and could predict the nutrition status of patients and disease prognosis. We aimed to explore the feasibility of predicting PhA-diagnosed malnutrition using facial image information based on deep learning (DL). METHODS: From August 2021 to April 2022, inpatients were enrolled from surgery, gastroenterology, and oncology departments in a tertiary hospital. Subjective global assessment was used as the gold standard of malnutrition diagnosis. The highest Youden index value was selected as the PhA cutoff point. We developed a multimodal DL framework to automatically analyze the three-dimensional (3D) facial data and accurately determine patients' PhA categories. The framework was trained and validated using a cross-validation approach and tested on an independent dataset. RESULTS: Four hundred eighty-two patients were included in the final dataset, including 176 with malnourishment. In male patients, the PhA value with the highest Youden index was 5.55°, and the area under the receiver operating characteristic curve (AUC) = 0.68; in female patients, the PhA value with the highest Youden index was 4.88°, and AUC = 0.69. Inpatients with low PhA had higher incidence of infectious complications during the hospital stay (P = 0.003). The DL model trained with 4096 points extracted from 3D facial data had the best performance. The algorithm showed fair performance in predicting PhA, with an AUC of 0.77 and an accuracy of 0.74. CONCLUSION: Predicting the PhA of inpatients from facial images is feasible and can be used for malnutrition assessment and prognostic prediction.

Neuroanatomical photogrammetric models using smartphones: a comparison of apps.

OBJECTIVES: A deep knowledge of the surgical anatomy of the target area is mandatory for a successful operative procedure. For this purpose, over the years, many teaching and learning methods have been described, from the most ancient cadaveric dissection to the most recent virtual reality, each with their respective pros and cons. Photogrammetry, an emergent technique, allows for the creation of three-dimensional (3D) models and reconstructions. Thanks to the spreading of photogrammetry nowadays it is possible to generate these models using professional software or even smartphone apps. This study aims to compare the neuroanatomical photogrammetric models generated by the two most utilized smartphone applications in this domain, Metascan and 3D-Scanner, through quantitative analysis. METHODS: Two human head specimens (four sides) were examined. Anatomical dissection was segmented into five stages to systematically expose well-defined structures. After each stage, a photogrammetric model was generated using two prominent smartphone applications. These models were then subjected to both quantitative and qualitative analysis, with a specific focus on comparing the mesh density as a measure of model resolution and accuracy. Appropriate consent was obtained for the publication of the cadaver's image. RESULTS: The quantitative analysis revealed that the models generated by Metascan app consistently demonstrated superior mesh density compared to those from 3D-Scanner, indicating a higher level of detail and potential for precise anatomical representation. CONCLUSION: Enabling depth perception, capturing high-quality images, offering flexibility in viewpoints: photogrammetry provides researchers with unprecedented opportunities to explore and understand the intricate and magnificent structure of the brain. However, it is of paramount importance to develop and apply rigorous quality control systems to ensure data integrity and reliability of findings in neurological research. This study has demonstrated the superiority of Metascan in processing photogrammetric models for neuroanatomical studies.

Spatio-temporal Relationship between Three-Dimensional Deformations of a Collapsible Tube and the Downstream Flowfield.

The interactions between fluid flow and structural components of collapsible tubes are representative of those in several physiological systems. Although extensively studied, there exists a lack of characterization of the three-dimensionality in the structural deformations of the tube and its influence on the flow field. This experimental study investigates the spatio-temporal relationship between 3D tube geometry and the downstream flow field under conditions of fully open, closed, and slamming-type oscillating regimes. A methodology is implemented to simultaneously measure three-dimensional surface deformations in a collapsible tube and the corresponding downstream flow field. Stereophotogrammetry was used to measure tube deformations, and simultaneous flow field measurements included pressure and planar Particle Image Velocimetry (PIV) data downstream of the collapsible tube. The results indicate that the location of the largest collapse in the tube occurs close to the downstream end of the tube. In the oscillating regime, sections of the tube downstream of the largest mean collapse experience the largest oscillations in the entire tube that are completely coherent and in phase. At a certain streamwise distance upstream of the largest collapse, a switch in the direction of oscillations occurs with respect to those downstream. Physically, when the tube experiences constriction downstream of the location of the largest mean collapse, this causes the accumulation of fluid and build-up of pressure in the upstream regions and an expansion of these sections. Fluctuations in the downstream flow field are significantly influenced by tube fluctuations along the minor axes. The fluctuations in the downstream flowfield are influenced by the propagation of disturbances due to oscillations in tube geometry, through the advection of fluid through the tube. Further, the manifestation of the LU-type pressure fluctuations is found to be due to the variation in the propagation speed of the disturbances during the different stages within a period of oscillation of the tube.

Unsupervised and interpretable discrimination of lithium-bearing minerals with Raman spectroscopy imaging.

As lithium-bearing minerals become critical raw materials for the field of energy storage and advanced technologies, the development of tools to accurately identify and differentiate these minerals is becoming essential for efficient resource exploration, mining, and processing. Conventional methods for identifying ore minerals often depend on the subjective observation skills of experts, which can lead to errors, or on expensive and time-consuming techniques such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Optical Emission Spectroscopy (ICP-OES). More recently, Raman Spectroscopy (RS) has emerged as a powerful tool for characterizing and identifying minerals due to its ability to provide detailed molecular information. This technique excels in scenarios where minerals have similar elemental content, such as petalite and spodumene, by offering distinct vibrational information that allows for clear differentiation between such minerals. Considering this case study and its particular relevance to the lithium-mining industry, this manuscript reports the development of an unsupervised methodology for lithium-mineral identification based on Raman Imaging. The deployed machine-learning solution provides accurate and interpretable results using the specific bands expected for each mineral. Furthermore, its robustness is tested with additional blind samples, providing insights into the unique spectral signatures and analytical features that enable reliable mineral identification.

Comparative Evaluation of the Performance of a Mobile Device Camera and a Full-Frame Mirrorless Camera in Close-Range Photogrammetry Applications.

The comparative evaluation of the performance of a mobile device camera and an affordable full-frame mirrorless camera in close-range photogrammetry applications involves assessing the capabilities of these two types of cameras in capturing images for 3D measurement purposes. In this study, experiments are conducted to compare the distortion levels, the accuracy performance, and the image quality of a mobile device camera against a full-frame mirrorless camera when used in close-range photogrammetry applications in various settings. Analytical methodologies and specialized digital tools are used to evaluate the results. In the end, generalized conclusions are drawn for using each technology in close-range photogrammetry applications.

Validation of inertial measurement units based on waveform similarity assessment against a photogrammetry system for gait kinematic analysis.

When assessing gait analysis outcomes for clinical use, it is indispensable to use an accurate system ensuring a minimal measurement error. Inertial Measurement Units (IMUs) are a versatile motion capture system to evaluate gait kinematics during out-of-lab activities and technology-assisted rehabilitation therapies. However, IMUs are susceptible to distortions, offset and drifting. Therefore, it is important to have a validated instrumentation and recording protocol to ensure the reliability of the measurements, to differentiate therapy effects from system-induced errors. A protocol was carried out to validate the accuracy of gait kinematic assessment with IMUs based on the similarity of the waveform of concurrent signals captured by this system and by a photogrammetry reference system. A gait database of 32 healthy subjects was registered synchronously with both devices. The validation process involved two steps: 1) a preliminary similarity assessment using the Pearson correlation coefficient, and 2) a similarity assessment in terms of correlation, displacement and gain by estimating the offset between signals, the difference between the registered range of motion (∆ROM), the root mean square error (RMSE) and the interprotocol coefficient of multiple correlation (CMCP). Besides, the CMCP was recomputed after removing the offset between signals (CMCPoff). The correlation was strong (r > 0.75) for both limbs for hip flexion/extension, hip adduction/abduction, knee flexion/extension and ankle dorsal/plantar flexion. These joint movements were studied in the second part of the analysis. The ∆ROM values obtained were smaller than 6°, being negligible relative to the minimally clinically important difference (MCID) estimated for unaffected limbs, and the RMSE values were under 10°. The offset for hips and ankles in the sagittal plane reached -9° and -8°, respectively, whereas hips adduction/abduction and knees flexion/extension were around 1°. According to the CMCP, the kinematic pattern of hip flexion/extension (CMCP > 0.90) and adduction/abduction (CMCP > 0.75), knee flexion/extension (CMCP > 0.95) and ankle dorsi/plantar flexion (CMCP > 0.90) were equivalent when captured by each system synchronously. However, after offset correction, only hip flexion/extension (CMCPoff = 1), hip adduction/abduction (CMCPoff > 0.85) and knee flexion/extension (CMCPoff > 0.95) satisfied the conditions to be considered similar.

High-resolution multispectral and RGB dataset from UAV surveys of ten cocoa agroforestry typologies in Côte d'Ivoire.

This paper introduces a dataset of aerial imagery captured during the 2022 cocoa growing season in the central-western region of Côte d'Ivoire. The images were acquired using a multispectral camera mounted on a DJI Phantom 4 unmanned aerial vehicle (UAV). The agricultural land surveyed encompasses 10 different types of cocoa-based agroforestry systems, each ranging from 2.6 ha to 8.3 ha, totaling 7638 images and covering 30 ha. The UAV mission was conducted at an altitude of 80 m, with a side overlap of 70 % and a front overlap of 80 %. This configuration achieved ground sampling distances (GSD) ranging from 4.2 to 4.6 cm providing high-resolution detailed imagery of those lands. These high-resolution RGB and multispectral images can be used to characterize the structural complexity of the systems as well as the abundance, and the health of the trees in these cocoa-based systems. It can be a valuable resource for researchers in the fields of ecology, agriculture, and environmental monitoring. The dataset supports a wide range of applications, from precision agriculture to sustainable cocoa land use management, making it a pivotal tool for enhancing agricultural practices and ecosystem management in Ivorian regions facing environmental and economic challenges.

Single-camera photogrammetry using a mobile phone for low-cost documentation of corpses.

Photogrammetry is a technique for studying and defining objects' shape, dimension, and position in a three-dimensional space using measurements obtained from two-dimensional photographs. It has gained popularity following the development of computer graphics technologies and has been applied to various branches of medicine. In this study, the authors present a method for low-cost photorealistic documentation of corpses during autopsy using single-camera photogrammetry with a mobile phone. Besides representing the body by demonstrating the injured and non-injured body parts as control, evidencing the body parts on a 3D reconstruction allows easy explanation to nonmedical experts such as lawyers.

Real-Time Spatial Mapping in Architectural Visualization: A Comparison among Mixed Reality Devices.

Recent advancements in communication technology have catalyzed the widespread adoption of realistic content, with augmented reality (AR) emerging as a pivotal tool for seamlessly integrating virtual elements into real-world environments. In construction, architecture, and urban design, the integration of mixed reality (MR) technology enables rapid interior spatial mapping, providing clients with immersive experiences to envision their desires. The rapid advancement of MR devices, or devices that integrate MR capabilities, offers users numerous opportunities for enhanced entertainment experiences. However, to support designers at a high level of expertise, it is crucial to ensure the accuracy and reliability of the data provided by these devices. This study explored the potential of utilizing spatial mapping within various methodologies for surveying architectural interiors. The objective was to identify optimized spatial mapping procedures and determine the most effective applications for their use. Experiments were conducted to evaluate the interior survey performance, using HoloLens 2, an iPhone 13 Pro for spatial mapping, and photogrammetry. The findings indicate that HoloLens 2 is most suited for the tasks examined in the scope of these experiments. Nonetheless, based on the acquired parameters, the author also proposes approaches to apply the other technologies in specific real-world scenarios.

Thermal Deformation Measurement of the Surface Shape of a Satellite Antenna Using High-Accuracy Close-Range Photogrammetry.

To determine both the size of a satellite antenna and the thermal deformation of its surface shape, a novel high-accuracy close-range photogrammetric technique is used in this study. The method is also applied to assess the performance of the antenna in orbit. The measurement principle and solution method of close-range photogrammetry were thoroughly investigated, and a detailed measurement test scheme was developed. A thermal deformation measurement of the surface shape of a satellite antenna was then carried out. The results show that the measurement error using close-range photogrammetry was smaller than 0.04 mm, which meets the accuracy requirement. Thanks to the high accuracy, it was discovered that both the surface shape and the rib precision of the satellite antenna deteriorate with decreasing temperature. The accuracy of the surface shape and ribs was lowest when the temperature node was -60 °C. The maximum root mean square errors (RMSEs) reached 0.878 mm and 0.761 mm, respectively. This indicates that the surface shape deformation error of the antenna caused by high and low temperatures is relatively high. However, the requirement for the technical design index (RMSE ≤ 1 mm for the surface shape accuracy of the antenna) is still met. Furthermore, for temperature differences of 40 °C and 80 °C, the measured RMSEs for the surface shape deformation were 0.216 mm and 0.411 mm, respectively. Overall, the technical design indicators (RMSE ≤ 0.3 mm and RMSE ≤ 0.5 mm, respectively) for the surface shape deformation of the antennas are met.

Ant3D-A Fisheye Multi-Camera System to Survey Narrow Spaces.

Although the field of geomatics has seen multiple technological advances in recent years which enabled new applications and simplified the consolidated ones, some tasks remain challenging, inefficient, and time- and cost-consuming. This is the case of accurate tridimensional surveys of narrow spaces. Static laser scanning is an accurate and reliable approach but impractical for extensive tunnel environments; on the other hand, portable laser scanning is time-effective and efficient but not very reliable without ground control constraints. This paper describes the development process of a novel image-based multi-camera system meant to solve this specific problem: delivering accurate, reliable, and efficient results. The development is illustrated from the system conceptualization and initial investigations to the design choices and requirements for accuracy. The resulting working prototype has been put to the test to verify the effectiveness of the proposed approach.

High-resolution elevation models of Larsen B glaciers extracted from 1960s imagery.

Accelerated warming since the 1950s has caused dramatic change to ice shelves and outlet glaciers on the Antarctic Peninsula. Long observational records of ice loss in Antarctica are rare but essential to accurately inform mass balance estimates of glaciers. Here, we use aerial images from 1968 to reveal glacier configurations in the Larsen B region. We use structure-from-motion photogrammetry to construct high-resolution (3.2 m at best) elevation models covering up to 91% of Jorum, Crane, Mapple, Melville and Flask Glaciers. The historical elevation models provide glacier geometries decades before the Larsen B Ice Shelf collapse in 2002, allowing the determination of pre-collapse and post-collapse elevation differences. Results confirm that these five tributary glaciers of the former Larsen B Ice Shelf were relatively stable between 1968 and 2001. However, the net surface elevation differences over grounded ice between 1968 and 2021 equate to 35.3 ± 1.2 Gt of ice loss related to dynamic changes after the ice shelf removal. Archived imagery is an underutilised resource in Antarctica and was crucial here to observe glacier geometry in high-resolution decades before significant changes to ice dynamics.

Some reef-building corals only disperse metres per generation.

Understanding the dispersal potential of different species is essential for predicting recovery trajectories following local disturbances and the potential for adaptive loci to spread to populations facing extreme environmental changes. However, dispersal distances have been notoriously difficult to estimate for scleractinian corals, where sexually (as gametes or larvae) or asexually (as fragments or larvae) derived propagules disperse through vast oceans. Here, we demonstrate that generational dispersal distances for sexually produced propagules can be indirectly inferred for corals using individual-based isolation-by-distance (IbD) analyses by combining reduced-representation genomic sequencing with photogrammetric spatial mapping. Colonies from the genus Agaricia were densely sampled across plots at four locations and three depths in Curaçao. Seven cryptic taxa were found among the three nominal species (Agaricia agaricites, Agaricia humilis and Agaricia lamarcki), with four taxa showing generational dispersal distances within metres (two taxa within A. agaricites and two within A. humilis). However, no signals of IbD were found in A. lamarcki taxa and thus these taxa probably disperse relatively longer distances. The short distances estimated here imply that A. agaricites and A. humilis populations are reliant on highly localized replenishment and demonstrate the need to estimate dispersal distances quantitatively for more coral species.