Realistic 3D Model Research Articles

Modern damage measurement of structural elements: Experiment, terrestrial laser scanning, and numerical studies

In this modern era of civilization, with the rise of construction of structures worldwide, there has been an increasing demand for structural health monitoring and assessment, which ensures the durability and stability of structural life. Terrestrial laser scanner (TLS) is one of those state-of-the-art technologies which has simplified the structural survey and assessment. TLS can rapidly acquire millions of 3D data points from an entire structural surface with high precision in a short period of time, encompassing the physical position and geometrical details of the subjected object in the form of a digital replica known as Digital Twin (DT). A Digital Twin is the set of all digitally represented data, which can greatly benefit engineers in terms of generating a realistic 3D model of the structure and identifying the structural deformities such as deformations, displacements, surface anomalies/irregularities, etc. Despite the significant benefit of this technology, there has been limited research studies on its application and evaluation in terms of accuracy in structural monitoring and assessment. Therefore, this research paper aims to provide an experimental program that not only measures and quantifies the performance of TLS, but also evaluates its accuracy in comparison to other conventional single-point measurement equipment. In this regard, a simply supported structural beam has been considered as a structural object and subjected to monotonic loading. Meanwhile, the deformation of the beam has been captured using a few methods including TLS. The finding of this research showed that the TLS performed remarkable well with errors less than 2% compared to other accurate approaches of measurements.

A Computational Fluid Dynamics Study to Compare Two Types of Arterial Cannulae for Cardiopulmonary Bypass

Thanks to recent technological and IT advances, there have been rapid developments in biomedical and health research applications of computational fluid dynamics. This is a methodology of computer-based simulation that uses numerical solutions of the governing equations to simulate real fluid flows. The aim of this study is to investigate, using a patient-specific computational fluid dynamics analysis, the hemodynamic behavior of two arterial cannulae, with two different geometries, used in clinical practice during cardiopulmonary bypass. A realistic 3D model of the aorta is extracted from a subject’s CT images using segmentation and reverse engineering techniques. The two cannulae, with similar geometry except for the distal end (straight or curved tip), are modeled and inserted at the specific position in the ascending aorta. The assumption of equal boundary conditions is adopted for the two simulations in order to analyze only the effects of a cannula’s geometry on hemodynamic behavior. Simulation results showed a greater percentage of the total output directed towards the supra-aortic vessels with the curved tip cannula (66% vs. 54%), demonstrating that the different cannula tips geometry produces specific advantages during cardiopulmonary bypass. Indeed, the straight one seems to generate a steadier flow pattern with good recirculation in the ascending aorta.

Predicting 3D particles shapes based on 2D images by using convolutional neural network

In order to accurately determine the three-dimensional (3D) shape of granular particles, one laborious approach is to employ X-ray microtomography and image processing techniques. As an alternative, in this study a 3D convolutional neural network (3D-CNN) methodology is presented to generate realistic 3D models of particles from a number of distinct two-dimensional (2D) projections. Initially, 3D synthetic particles with the targeted statistical distributions of the relevant geometric parameters, such as sphericity, elongation, aspect ratio, and flatness, were randomly generated using Fourier shape descriptors (FSDs). The database based on the statistical distributions of geometric parameters of Avicel® PH 200, obtained through dynamic image analysis. Following that, projections from multiple angles of 2D particle images were extracted for model training. By using a convolutional neural network (CNN) the shape of the particles was predicted, which involves the following sequential steps: a) model training on 2D images; b) a decoder is built to generate the 3D voxel model after an encoder extracts the properties of 2D images; c) a marching cube algorithm that converts the particle 3D voxel model into a mesh model; d) the accuracy of the prediction is evaluated by comparing the geometric parameters of the prediction models that were generated by using FSDs. The methodology was validated using a database of 3D synthetic particles with targeted statistical distributions of geometric parameters, such as sphericity, elongation, aspect ratio, and flatness. The mean absolute percentage error (MAPE) of the AI model for these parameters was 2.24%, 7.01%, 10.93%, and 7.67%, respectively. The 3D-CNN methodology has the potential for broad applications in various fields, such as rock and mineral analysis, battery materials, pharmaceuticals, and space exploration, offering a practical and affordable solution for shape analysis of relevant materials. It can significantly improve the efficiency and accuracy of numerical simulations and analyses, leading to new insights and innovations in a wide range of fields.

260 Development of self-made realistic 3D human models of cardiac arrests for emergency medical education

260 Development of self-made realistic 3D human models of cardiac arrests for emergency medical education

Calibration of DART 3D model with UAV and Sentinel-2 for studying the radiative budget of conventional and agro-ecological maize fields

Quantifying the radiative budget (RB) of maize, the world's predominant cereal, is crucial to managing its growth in a context of global warming. Its microclimate including temperature, water, and energy flux depend on crop management practices. This paper compares the influence of agroecological practices (AE) and conventional agriculture (CA) on the RB of maize using three-dimensional (3D) radiative transfer modelling and remote sensing (RS) observations. We studied two neighbour maize fields in south-west France, respectively with AE and CA practices. Time series of photosynthetically active radiation absorbed (APAR) by plants (APARplant) and soil (APARsoil) were simulated with the DART radiative transfer model. First, realistic 3D models of the CA and AE fields were created and validated with a new method based on DART and Sentinel 2 and UAV reflectance and vegetation indices acquired in July 2019. At that date, around midday, APARplant was larger by 21.5 W/m2 in the AE field and APARsoil was larger by 20.1 W/m2 in the CA field. We explained these differences by differences in geometric and optical parameters (OP) between the two fields. OPsoil causes ≈45% of the differences in APARplant and APARsoil. The shape of plant causes ≈14% of the difference in APARplant and ≈17% in APARsoil. OPplant causes ≈14% of the difference in APARplant and ≈1% in APARsoil. Field geometry (row orientation, inter-row and plant distance) causes ≈7% of the difference in APARplant and 2% in APARsoil. It stresses the great role of OPsoil associated to AE practices. Because it integrates the non-linear effects of all above parameters, the LAI (Leaf Area Index) accounts for ≈40% difference in APARplant and APARsoil. The sensitivity of APAR to LAI is twice as low in the AE field than in the CA field. We showed that APAR differences between the AE and CA fields can be even greater with other maize row orientations. We also highlighted the role of the field model on simulated APAR by comparing the use of APAR simulated by a 3D field model and its corresponding 1D turbid field: 1D turbid models resulted in a 16% increase in APARplant and in similar APARsoil, compared to the 3D CA and AE models.

Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study

Objective. Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices. Approach. Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair. Main results. The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values. Significance. For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm−1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.

Antiproliferative Imidazo-Pyrazole-Based Hydrogel: A Promising Approach for the Development of New Treatments for PLX-Resistant Melanoma.

Aiming at developing a dermal formulation against melanoma, the synthesized imidazo-pyrazoles 2-phenyl-2,3-dihydro-1H-imidazo[1,2-b]pyrazole-7-carboxylic acid (3-methoxy-4-phenoxy-benzylidene)-hydrazide (4G) and 2-phenyl-2,3-dihydro-1H-imidazo[1,2-b]pyrazole-7-carboxylic acid (4-benzyloxy-3-methoxy-benzylidene)-hydrazide (4I) were screened on patient-isolated melanoma cells (MEOV NT) and on Vemurafenib (PLX4032)-resistant (MEOV PLX-R) ones. Since 4I on MEOV PLX-R cells was 1.4-fold more effective than PLX, a hydrogel formulation containing 4I (R4HG-4I) was prepared in parallel with an empty R4-based hydrogel (R4HG) using a synthesized antibacterial resin (R4) as gelling agent. Thanks to its high hydrophilicity, porosity (85%), and excellent swelling capability (552%), R4 allowed to achieve R4HG and R4HG-4I with high equilibrium degree of swelling (EDS) and equilibrium water content (EWC). Chemometric-assisted ATR-FTIR analyses confirmed the chemical structure of swollen and fully dried (R4HG-D and R4HG-4I-D) hydrogels. The morphology of R4HG-D and R4HG-4I-D was examined by optical microscopy and SEM, while UV-vis analyses were carried out to obtain the drug loading (DL%) and the encapsulation efficiency (EE%) of R4HG-4I. Potentiometric titrations were performed to determine the equivalents of NH3+ in both R4HG and R4HG-4I. The swelling and water release profiles of both materials and related kinetics were assessed by equilibrium swelling rate and water loss studies, respectively, while their biodegradability over time was assessed by in vitro degradation experiments determining their mass loss. Rheological experiments established that both R4HG and R4HG-4I are shear-thinning Bingham pseudoplastic fluids with low yield stress, thus assuring easy spreadability in a future topical application. Release studies evidenced a sustained and quantitative release of 4I governed mainly by diffusion. Upon favorable results from further experiments in a more realistic 3D model of melanoma, R4HG-4I could represent a starting point to develop new topical therapeutic options to adjuvate the treatments of melanoma cells also when resistant to currently available drugs.

A Three-Dimensional Full-Coverage Operation Path Planning Method for Plant Protection Unmanned Aerial Vehicles Based on Energy Consumption Modeling

With the rapid development of precision agriculture technology worldwide, plant protection unmanned aerial vehicles (UAVs) have been widely applied in the prevention and control of agricultural pests and diseases due to their advantages such as unrestricted terrain, strong maneuverability, hover capability, and high operational efficiency. In view of the fact that most of the current path planning methods for plant protection UAVs are mainly applicable to large fields with relatively flat terrain, and there is a lack of three-dimensional path planning methods applicable to hilly orchards, as well as a lack of intuitive evaluation of the advantages and disadvantages of the paths by utilizing the amount of energy consumption, this paper proposes a three-dimensional (3D) path planning method for plant protection UAVs in hilly orchards. The method utilizes the three-dimensional (3D) coordinates of the operational area obtained from a realistic 3D model of the area, and determines the 3D operational path through the use of Boustrophedon Cellular Decomposition and the height variations of the operational area. Based on the induced power used by the plant protection UAV for flight and the power needed to overcome wind resistance, combined with the change of the load of the plant protection UAV and the supply situation, the relative energy consumption model of the plant protection UAV is constructed. Then, by optimizing the operational heading angle (1–180°), the 3D path with the minimum relative energy consumption is obtained. Through a simulation test, it is demonstrated that the path with the minimum relative energy consumption (operational heading angle of 133°) reduces the average relative energy consumption by 62.44% and 47.21% compared to the path with the maximum relative energy consumption (operational heading angle of 51°) and the average relative energy consumption, respectively. This proves the feasibility of the proposed path planning method in hilly orchard environments and provides a reference for the application of plant protection UAVs in such orchards.

The Beating Heart of Untapped Business Opportunities for Additive Manufacturing.

This article presents a case that joins user-driven innovation and additive manufacturing (AM) towards latent business opportunities in the preparation for life threatening operations. Surgeons, confronted with a patient with a delicate heart condition, collaborated with a prototyping facility to print a realistic 3D model of the patient's aortic aneurysm. The model allowed the surgeons to first study and then experiment to determine the most effective operation procedure before the actual operation, which shortened the surgery time by approximately 70%. Reducing surgery time creates two forms of value: improving patient outcomes and reducing costs. Shorter times under anesthetic and on cardiopulmonary bypass correlate with better surgical results. Reducing healthcare costs brings broad societal benefits in both publicly and privately funded healthcare systems. We outline a case for makerspaces to capture value by joining their expertise and manufacturing equipment with the needs of nearby healthcare systems for novel business developments.

Projection of realistic three-dimensional photogrammetry models using stereoscopic display: A technical note.

The 3D stereoscopic technique consists in providing the illusional perception of depth of a given object using two different images mimicking how the right and left eyes capture the object. Both images are slightly different and when overlapped gives a three-dimensional (3D) experience. Considering the limitations for establishing surgical laboratories and dissections courses in some educational institutions, techniques such as stereoscopy and photogrammetry seem to play an important role in neuroanatomy and neurosurgical education. The aim of this study was to describe how to combine and set up realistic models acquired with photogrammetry scans in 3D stereoscopic projections. Three donors, one dry skull, embalmed brain and head, were scanned using photogrammetry. The software used for displaying the final realistic 3D models (Blender, Amsterdam, the Netherlands) is a free software and allows stereoscopic projection without compromising the interactivity of each model. By default, the model was exported and immediately displayed as a red cyan 3D mode. The 3D projector used in the manuscript required a side-by-side 3D mode which was set up with simple commands on the software. The final stereoscopy projection offered depth perception and a visualization in 360° of each donor; this perception was noted especially when visualizing donors with different cavities and fossae. The combination of 3D techniques is of paramount importance for neuroanatomy education. Stereoscopic projections could provide a valuable tool for neuroanatomy instruction directed at clinical trainees and could be especially useful when access to laboratory-based learning is limited.

Retracted: Application of Realistic 3D Model in Building Prefabricated Nanomaterial Structure.

[This retracts the article DOI: 10.1155/2022/1726948.].

Average molecular structure model of shale kerogen: Experimental characterization, structural reconstruction, and pyrolysis analysis

Shale can be both a source rock and a reservoir rock, which is a typical self-generating and self-storing type of oil accumulation. Its main organic component is kerogen. Using molecular dynamics (MD), a realistic kerogen molecular structure model is an alternative to experimental and analytical-only approaches for studying shale organic matter's microscopic properties. Therefore, it is useful to establish an average molecular structure model for shale kerogen. Moreover, the pyrolysis mechanism of shale kerogen is of great significance for developing and utilizing shale mineral resources. In this study, geochemical and spectroscopic measurements such as the elemental analysis, 13C nuclear magnetic resonance spectroscopy (13C NMR), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) were used to obtain information about the carbon skeleton, aliphatic structures, and aromatic structures of the kerogen. Following information analysis and molecular fragment splicing, a 2D molecular structure model of kerogen from the Nanpu shale, with the chemical formula C199H240O20N6S2 and molecular weight of 3096 Daltons was constructed. After that, the accuracy of the 2D structure was verified by comparing the 13C NMR spectra simulated by the 2D structure to the experimental spectra. Using MD simulation, based on the kerogen density, 10 2D structures are then combined to create a realistic 3D molecular structure model of kerogen. Finally, pyrolysis analysis was performed based on the established 3D molecular structure model of kerogen to determine the effect of temperature on pyrolysis. Using the advantages of various technologies, this study not only provides a systematic method for establishing a realistic 3D molecular structure model of kerogen but also contributes to in-depth research on the reaction mechanism of kerogen pyrolysis, providing a reliable foundation for future research on the properties of shale at the molecular scale.

Application of Airborne RadarTechnology in DEM Production

Since its appearance, airborne laser scanning technology has become more convenient and modern with the continuous progress and development of science and technology. Airborne LiDAR has a very wide range of applications in various fields. It can obtain the three-dimensional coordinates of the measured object comprehensively and with high quality. It has the advantages of high efficiency and high precision in DEM production. In this paper, DEM is produced in an area near Guantao County, Handan City. Firstly, airborne LiDAR is used to collect 3D laser point cloud data, and then software is used to process the point cloud. TerraSolid software is used to perform coordinate conversion and point cloud classification on the point cloud, and finally DEM is produced on the classified ground points. The result is a realistic and intuitive 3D model. The results show that the 3D point cloud data collected by airborne LiDAR can fully and accurately reflect the topographic and geomorphic information, and the software tools and algorithms in the processing process can effectively improve the availability and accuracy of the data, and the generated DEM data can provide important data support for terrain analysis, urban planning, natural resource management and other fields.

Discrimination of facial identity based on simple contrast patterns generated by shading and shadows

The pattern of shadows and shading across a face is determined partly by face shape and may therefore provide a cue for facial recognition. In this study, we measured the ability of human observers to discriminate facial identity based simply on the coarse pattern of contrast produced by the interaction between facial geometry and lighting direction. We used highly realistic 3D models of human heads to create images of faces illuminated from different horizontal and vertical directions, which were then converted to two-tone images (‘Mooney faces’) to isolate the coarse pattern of contrast. Participants were presented with pairs of two-tone faces and judged whether it was the same person in both images. Participants could discriminate facial identity based on the minimal cues within the two-tone images, though sensitivity depended on the horizontal and vertical lighting direction. Performance on the Mooney recognition task correlated with general facial recognition ability, though the role of face-specific processing in this relationship was not significant. Our results demonstrate that shading information in the form of simple contrast cues is sufficient for discriminating facial identity, and support the idea that visual processing is somewhat optimised for overhead lighting – here, in the relatively high-level context of face identity recognition.

Assessment of 3D Model for Photogrammetric Purposes Using AI Tools Based on NeRF Algorithm

The aim of the paper is to analyse the performance of the Neural Radiance Field (NeRF) algorithm, implemented in Instant-NGP software, for photogrammetric purposes. To achieve this aim, several datasets with different characteristics were analysed, taking into account object size, image acquisition technique and geometric configuration of the images. The NeRF algorithm proved to be effective in the construction of the 3D models; in other words, in Instant-NGP it was possible to obtain realistic 3D models in a detailed manner and very quickly, even in rather weak geometric configurations of the images. The performance obtained in the latter environment was compared with that achieved by two software packages, one widely used in the photogrammetric field, Agisoft Metashape, and one open source, Colmap. The comparison showed encouraging results in building 3D models, especially under weak geometry conditions; although, the geometric description of objects under point clouds or meshes needs improvement for use in the photogrammetric field.

Impact of virtual reality training on mastoidectomy performance: a prospective randomised study

PurposeThe opportunities for surgical training and practice in the operating room are in decline due to limited resources, increased efficiency demands, growing complexity of the cases, and concerns for patient safety. Virtual reality (VR) offers a novel opportunity to enhance surgical training and provide complementary three-dimensional experience that has been usually available in the operating room. Since VR allows viewing and manipulation of realistic 3D models, the VR environment could enhance anatomical and topographical knowledge, in particular. In this study, we explored whether incorporating VR anatomy training improves novices’ performance during mastoidectomy over traditional methods.MethodsThirty medical students were randomized into two groups and taught mastoidectomy in a structured manner. One group utilized a VR temporal bone model during the training while the other group used more traditional materials such as anatomy books. After the training, all participants completed a mastoidectomy on a 3D-printed temporal bone model under expert supervision. Performance during the mastoidectomy was evaluated with multiple metrics and feedback regarding the two training methods was gathered from the participants.ResultsThe VR training method was rated better by the participants, and they also needed less guidance during the mastoidectomy. There were no significant differences in operational time, the occurrence of injuries, self-assessment scores, and the surgical outcome between the two groups.ConclusionOur results support the utilization of VR training in complete novices as it has higher trainee satisfaction and leads to at least as good results as the more traditional methods.

Virtual reality-based training and pre-operative planning for head and neck sentinel lymph node biopsy

ObjectiveSentinel lymph node biopsy (SLNB) is crucial for managing head and neck skin cancer. However, variable lymphatic drainage can complicate SLN detection when using Single-Photon Emission Computed Tomography (SPECT) or lymphoscintigraphy. Virtual Reality (VR) can contribute to pre-operative planning by simulating a realistic 3D model, which improves orientation. VR can also facilitate real-patient training outside the operating room. This study explored using a VR platform for pre-operative planning in head and neck skin cancer patients undergoing SLNBs and assessed its value for residential training. Materials and methodsIn this prospective technology pilot study, attending surgeons and residents who performed 21 SLNB operations on patients with head and neck skin cancers (81% males, mean age 69.2 ± 11.3) used a VR simulation model based on each patient's pre-operative SPECT scan to examine patient-specific anatomy. After surgery, they completed a questionnaire on the efficiency of the VR simulation as a pre-operative planning tool and training device for residents. ResultsThe attending surgeons rated the VR model's accuracy at 8.3 ± 1.6 out of 10. Three-quarters (76%) of residents reported increased confidence after using VR. The physicians rated the platform's contribution to residents' training at 7.4 ± 2.1 to 8.9 ± 1.3 out of 10. ConclusionA VR SLNB simulation can accurately portray marked sentinel lymph nodes. It was rated high as a surgical planning and teaching tool among attending surgeons and residents alike and may play a role in pre-operative planning and resident training. Further studies are needed to explore its applications in practice.

Impact of defect annihilation mechanism on the grain size dependence and the dimensionality effect of radiation induced segregation

Radiation-induced segregation (RIS) of alloying elements at defect sinks critically affects material performance. This work computes and compares RIS at grain boundaries in a Fe-Ni-Cr alloy for a wide range of grain sizes with 1D, 2D, and 3D models. A transition in grain size dependence from linear to gradual convergence is identified, along with a dimensionality effect in modeling RIS using 1D and 2D models compared with more realistic 3D models. Further analysis shows that both the grain size dependence and the dimensionality effect are governed by the defect annihilation mechanism. In the absorption dominated regime, 1D and 2D models overestimate RIS, and RIS depends linearly on grain size. In the recombination dominated regime, the dimensionality effect vanishes gradually, and RIS converges gradually over grain size. The dimensionality effect can be corrected using the ratio of recombination over sink absorption, allowing for realistic RIS simulation using the 1D model.

Urban Forest Above-Ground Biomass Estimation Based on UAV 3D Real Scene

(1) Background: A three-dimensional (3D) real scene is a digital representation of the multidimensional dynamic real-world structure that enables the realistic and stereoscopic expression of actual scenarios, and is an important technological tool for urban refinement management. The above-ground biomass (AGB) of urban forests is an important indicator that reflects the urban ecological environment; therefore, the accurate estimation of AGB is of great significance for evaluating urban ecological functions. (2) Methods: In this study, multiangle aerial photographs of urban street trees were obtained via an unmanned aerial vehicle (UAV) single-lens five-way flight, from 0°, 0°, 90°, 180°, 270°, and five other directions. The multiple view stereo (MVS) algorithm was used to construct three-dimensional realistic models of two tree species: ginkgo and camphor. Then, structural parameters such as tree height, crown diameter, and crown volume were estimated from the 3D real-scene models. Lastly, single-tree AGB models were developed based on structural parameters. (3) Results: The results of this study indicated the following: (A) The UAV visible-light realistic 3D model had clear texture and truly reflected the structural characteristics of two tree species, ginkgo and camphor. (B) There was a significant correlation between the reference tree height, crown diameter and crown volume obtained from the realistic 3D model and the measured values; the R2 for ginkgo height was 0.90, the R2 for camphor crown diameter was 0.87, and the R2 for ginkgo crown volume was 0.89. (C) The accuracy of the AGB estimation models constructed with tree height and canopy volume as variables was generally higher than that of models with tree height and canopy diameter; the model with the highest accuracy of AGB estimation for ginkgo was the linear model with a validation accuracy R2 of 0.96 and RMSE of 8.21 kg, while the model with the highest accuracy of AGB estimation for camphor was the quadratic polynomial model with a validation accuracy R2 of 0.92 and RMSE of 27.74 kg. (4) Conclusions: This study demonstrated that the UAV 3D real-scene model can achieve high accuracy in estimating single-wood biomass in urban forests. In addition, for both tree species, there was no significant difference between the AGB estimates based on the UAV 3D real scene and LiDAR and the measured AGB. These results of urban single-wood AGB estimation based on the UAV 3D real-scene model were consistent with those of LiDAR and even with the measured AGB. Therefore, based on the UAV 3D real-scene model, the single-wood biomass can be estimated with high accuracy. This represents a new technical approach to urban forest resource monitoring and ecological environment function evaluation.

FEW SHOT PHOTOGRAMETRY: A COMPARISON BETWEEN NERF AND MVS-SFM FOR THE DOCUMENTATION OF CULTURAL HERITAGE

Abstract. 3D documentation methods for Digital Cultural Heritage (DCH) domain is a field that becomes increasingly interdisciplinary, breaking down boundaries that have long separated experts from different domains. In the past, there has been an ambiguous claim for ownership of skills, methodologies, and expertise in the heritage sciences. This study aims to contribute to the dialogue between these different disciplines by presenting a novel approach for 3D documentation of an ancient statue. The method combines TLS acquisition and MVS pipeline using images from a DJI Mavic 2 drone. Additionally, the study compares the accuracy and final product of the Deep Points (DP) and Neural Radiance Fields (NeRF) methods, using the TLS acquisition as validation ground truth. Firstly, a TLS acquisition was performed on an ancient statue using a Faro Focus 2 scanner. Next, a multi-view stereo (MVS) pipeline was adopted using 2D images captured by a Mini-2 DJI Mavic 2 drone from a distance of approximately 1 meter around the statue. Finally, the same images were used to train and run the NeRF network after being reduced by 90%. The main contribution of this paper is to improve our understanding of this method and compare the accuracy and final product of two different approaches - direct projection (DP) and NeRF - by exploiting a TLS acquisition as the validation ground truth. Results show that the NeRF approach outperforms DP in terms of accuracy and produces a more realistic final product. This paper has important implications for the field of CH preservation, as it offers a new and effective method for generating 3D models of ancient statues. This technology can help to document and preserve important cultural artifacts for future generations, while also providing new insights into the history and culture of different civilizations. Overall, the results of this study demonstrate the potential of combining TLS and NeRF for generating accurate and realistic 3D models of ancient statues.