3D Mapping Research Articles

Remotely Powered Two-Wire Cooperative Sensors for Bioimpedance Imaging Wearables.

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size.

Coronary sinus signal amplitude: A predictor of the atrial substrate and low voltage areas.

Low voltage areas (LVA) are pivotal in atrial fibrillation (AF) pathogenesis, influencing local left atrial LA excitation and perpetuating AF occurrences. While pulmonary vein isolation (PVI) with cryo-balloon (CB) ablation is effective for AF, it doesn't provide insights into the LA substrate or detect LVA, which affects ablation success rates. This study examines whether LA voltage and LVAs can be anticipated by analyzing the voltage signal amplitude at the coronary sinus (CS) catheter, which is standard in CB and radiofrequency ablation procedures. A retrospective analysis of 284 patients with recurrent AF undergoing RF catheter ablation was conducted at a high-volume EP center in Germany. The correlation between LA voltage and LVA with the CS signal was explored. The signal amplitude in the CS significantly correlated with voltage in LA walls, particularly in the proximal CS (correlation coefficient ρ=0.81, p<0.001). A CS signal cut-off of 1.155mV effectively predicted severe atrial LVAs (>40%) with a sensitivity of 90.7% and a specificity of 100%. While a threshold of 1.945mV identified patients with no significant atrial LVAs (<5%) with a sensitivity of 88% and a specificity of 50% (AUC: 0.81, 95% CI: 0.71-0.89, p<0.001). The CS signal amplitude is associated with the LA voltage. Due to its potential as a diagnostic tool for atrial LVAs, the signal amplitude in the CS could provide valuable information about the LA substrate, especially when 3D mapping is not feasible.

Reduction in Olfactory Discomfort in Inhabited Premises from Areas with Mofettas through Cellulosic Derivative-Polypropylene Hollow Fiber Composite Membranes.

Hydrogen sulfide is present in active or extinct volcanic areas (mofettas). The habitable premises in these areas are affected by the presence of hydrogen sulfide, which, even in low concentrations, gives off a bad to unbearable smell. If the living spaces considered are closed enclosures, then a system can be designed to reduce the concentration of hydrogen sulfide. This paper presents a membrane-based way to reduce the hydrogen sulfide concentration to acceptable limits using a cellulosic derivative-propylene hollow fiber-based composite membrane module. The cellulosic derivatives considered were: carboxymethyl-cellulose (NaCMC), P1; cellulose acetate (CA), P2; methyl 2-hydroxyethyl-cellulose (MHEC), P3; and hydroxyethyl-cellulose (HEC), P4. In the permeation module, hydrogen sulfide is captured with a solution of cadmium that forms cadmium sulfide, usable as a luminescent substance. The composite membranes were characterized by SEM, EDAX, FTIR, FTIR 2D maps, thermal analysis (TG and DSC), and from the perspective of hydrogen sulfide air removal performance. To determine the process performances, the variables were as follows: the nature of the cellulosic derivative-polypropylene hollow fiber composite membrane, the concentration of hydrogen sulfide in the polluted air, the flow rate of polluted air, and the pH of the cadmium nitrate solution. The pertraction efficiency was highest for the sodium carboxymethyl-cellulose (NaCMC)-polypropylene hollow fiber membrane, with a hydrogen sulfide concentration in the polluted air of 20 ppm, a polluted air flow rate (QH2S) of 50 L/min, and a pH of 2 and 4. The hydrogen sulfide flux rates, for membrane P1, fall between 0.25 × 10-7 mol·m2·s-1 for the values of QH2S = 150 L/min, CH2S = 20 ppm, and pH = 2 and 0.67 × 10-7 mol·m-2·s-1 for the values of QH2S = 50 L/min, CH2S = 60 ppm, and pH = 2. The paper proposes a simple air purification system containing hydrogen sulfide, using a module with composite cellulosic derivative-polypropylene hollow fiber membranes.

Soliton and lump and travelling wave solutions of the (3 + 1) dimensional KPB like equation with analysis of chaotic behaviors

Nonlinear evolution equations (NLEEs) have a wide range of applications in various fields, including physics, engineering, biology, economics, and more. These equations are used to describe complex systems that change over time, where the state or behavior of the system not only depends on the current situation, but may also be related to the past. A deep understanding of the solutions to NLEEs is of great significance for predicting and controlling the behavior of complex systems. The (3 + 1)-dimensional Kadomtsev-Petviashvili-Boussinesq-like (KPB-like) equation represents a partial differential equation that describes nonlinear wave phenomena in multi-dimensional spaces. This model is commonly employed in fields such as fluid dynamics, plasma physics, and nonlinear optics to study wave behaviors. This paper investigates the KPB-like equations, which have meaningful physical implications in describing nonlinear wave phenomena. Hirota bilinear method is employed to derive the bilinear form for the KPB-like equation and 1-soliton, 2-soliton, lump, and travelling wave solutions are studied to this kind of nonlinear model. In addition, the chaotic behaviors of soliton and lump solutions are explored via applying the Duffing chaotic system. To have a better understanding of dynamic structures, 3D, line, density and contour map plots of begotten results are displayed. Our results indicate the directness and effectiveness of the applied method for analyzing high-dimensional differential equations that arise in nonlinear science.

Spatial chemistry of citrus reveals molecules bactericidal to Candidatus Liberibacter asiaticus

Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-infected trees. We demonstrate how spatial information from molecular maps of branches and single leaves yields insight into the biology not accessible otherwise. In particular, we found evidence that flavonoid biosynthesis is disrupted in HLB-infected trees, and an increase in the polyamine, feruloylputrescine, is highly correlated with an increase in disease severity. Based on mechanistic details revealed by these molecular maps, followed by metabolic modeling, we formulated and tested the hypothesis that CLas infection either directly or indirectly converts the precursor compound, ferulic acid, to feruloylputrescine to suppress the antimicrobial effects of ferulic acid and biosynthetically downstream flavonoids. Using in vitro bioassays, we demonstrated that ferulic acid and bioflavonoids are indeed highly bactericidal to CLas, with the activity on par with a reference antibiotic, oxytetracycline, recently approved for HLB management. We propose these compounds should be evaluated as therapeutics alternatives to the antibiotics for HLB treatment. Overall, the utilized 3D metabolic mapping approach provides a promising methodological framework to identify pathogen-specific inhibitory compounds in planta for potential prophylactic or therapeutic applications.

3D Mapping In Construction Projects for Soil Characterizations And EIA Enhancement

With the advancement on automation systems in our life and construction projects the development of automated Environmental Impact assessment EIA system is desirable. This could be achieved by set of integrated technologies, software, and hardware to perform a task which is in this research paper is Quality EIA. The environmental impact assessment must be improved, assessed, and quality checked for the human and the environment health and safety benefit first, and the advancement of human activities and needs towards the future. If we consider the development and construction projects is one of the markers and the signature of how far is countries and human civilized or advanced, the EIA quality review and development of this document in any project should be improved and advanced. Ideally EIA system, document, will lead to quickly and easily obtain information, improve project value, and return of investment, improving facilities and reach the optimum clients and government requirements. This often necessitates to build a tailored applications sometime combine or develop innovative, and integrate, new, existing hardware, software, methods, and technologies to reach that aim. Which is the research methodology of this research paper This research paper concluded that 3D mapping for soil characterizations a technology where spatial interpolation methods play a significant part as a backbone of its core in relation to the accuracy of the data which will provides essential elements towards site characterization information, that need to be informed in to the EIA in structure and elegant way to improve decision making, planning strategies, environmental management, risk assessment, more than those projects estimations. This research paper adopts a multi-method approach involving reviewing the literature, case studies, and computer simulation.

Development of an Automatic Feature Point Classification Method for Three-Dimensional Mapping Around Slewing and Derricking Cranes

Crane automation requires a three-dimensional (3D) map around cranes that should be reconstructed and updated quickly.In this study, a high-precision classification method was developed to distinguish stationary objects from moving objects in moving images captured by a monocular camera to stabilize 3D reconstruction. To develop the method, a moving image was captured while the crane was slewed with a monocular camera mounted vertically downward at the tip of the crane. The boom length and angle data were output from a control device, a controller area network. For efficient development, a simulator that imitated the environment of an actual machine was developed and used. The proposed method uses optical flow to track feature points. The classification was performed successfully, independent of derricking motion. Consequently, the proposed method contributes to stable 3D mapping around cranes in construction sites.

Hybrid Block Chaotic Compressive Sensing and Chaotic Scrambling Algorithms for Color Image Encryption System

This paper suggests a new image encryption algorithm based on block compressive sensing (BCS) and chaotic scrambling techniques. With compressive sensing (CS), signals can be sampled much lower than the Nyquist-Shannon rate while preserving their information content. BCS can be used as a one-step process by using a 3D logistic chaotic map, the measurement matrix is used as a secret key for encryption. BCS algorithm used an individual image reconstruction algorithm that leverages l_1norm minimization to promote signal sparsity, and a smoothing operator to enhance image quality. An encrypted image is first decomposed into three sub-images based on the tricolor theory; then, a discrete wavelet transform is used to sparsely process the three decomposed images. A 2D Henon map is used to scramble the compressed image after compression. This process further enhances the security of the system by increasing the complexity of the encryption process. The results showed that the proposed system provides better security and has a lower computational complexity than other methods. Furthermore, the proposed system is resistant to known attacks such as brute force and statistical attacks.

Early three-dimensional growth in uncomplicated type B aortic dissection is associated with long-term outcomes

ObjectiveLate adverse events (LAEs) are common among initially uncomplicated type B aortic dissection (uTBAD); however, identifying those patients at highest risk of LAEs remains a significant challenge. Early false lumen (FL) growth has been suggested to increase risk, but confident determination of growth is often hampered by error in two-dimensional clinical measurements. Semi-automated three-dimensional (3D) mapping of aortic growth, such as by vascular deformation mapping (VDM), can potentially overcome this limitation using computed tomography angiograms (CTA). We hypothesized that FL growth in the early pre-dissection phase by VDM can accurately predict LAEs. MethodsWe performed a two-center retrospective study of patients with uTBAD, with paired CTAs in the acute (1-14 days) and subacute/early chronic (1-6 months) periods. VDM analysis was used to map 3D growth. Standard clinical CT measures (ie, aortic diameters, tear characteristics) were also collected. Multivariate analysis was conducted using a decision tree and Cox proportional hazards model. LAEs were defined as aneurysmal FL (>55 mm); rapid growth (>5 mm within 6 months); aorta-specific mortality, rupture, or re-dissection. ResultsA total of 107 (69% male) patients with uTBAD initially met inclusion criteria with a median follow-up of 7.3 years (interquartile range [IQR], 4.7-9.9 years). LAEs occurred in 72 patients (67%) at 2.5 years (IQR, 0.7-4.8 years) after the initial event. A multivariate decision tree model identified VDM growth (>2.1 mm) and baseline diameter (>42.7 mm) as optimal predictors of LAEs (area under the receiver operating characteristic curve = 0.94), achieving an 87% accuracy (sensitivity of 93%, specificity of 76%) after leave-one-out validation. Guideline reported high-risk features were not significantly different between groups. ConclusionsEarly growth of the FL in uTBAD was the best tested indicator for LAEs and improves upon the current gold-standard of baseline diameter in selecting patients for early prophylactic thoracic endovascular aortic repair.

Imprints of the Local Bubble and Dust Complexity on Polarized Dust Emission

Using 3D dust maps and Planck polarized dust emission data, we investigate the influence of the 3D geometry of the nearby interstellar medium (ISM) on the statistics of the dust polarization on large ( 80′ ) scales. We test recent models that assume that the magnetic field probed by the polarized dust emission is preferentially tangential to the Local Bubble wall, but we do not find an imprint of the Local Bubble geometry on the dust polarization fraction. We also test the hypothesis that the complexity of the 3D dust distribution drives some of the measured variation of the dust polarization fraction. We compare sight lines with similar total column densities and find that, on average, the dust polarization fraction decreases when the dust column is substantially distributed among multiple components at different distances. Conversely, the dust polarization fraction is higher for sight lines where the dust is more concentrated in 3D space. This finding is statistically significant for the dust within 1.25 kpc, but the effect disappears if we only consider dust within 270 pc. In conclusion, we find that the extended 3D dust distribution, rather than solely the dust associated with the Local Bubble, plays a role in determining the observed dust polarization fraction at 80′. This conclusion is consistent with a simple analytical prediction and remains robust under various modifications to the analysis. These results illuminate the relationship between the 3D geometry of the ISM and tracers of the interstellar magnetic field. We discuss implications for our understanding of the polarized dust foreground to the cosmic microwave background.

Evaluation of Myocarditis with a Free-breathing 3D Isotropic Whole-Heart Joint T1 and T2 Mapping Sequence

BackgroundThe diagnosis of myocarditis by CMR requires the use of T2 and T1 weighted imaging, ideally incorporating parametric mapping. Current 2D mapping sequences are acquired sequentially and involve multiple breath-holds resulting in prolonged scan times and anisotropic image resolution. We developed an isotropic free-breathing 3D whole-heart sequence which allows simultaneous T1 and T2 mapping and validated it in patients with suspected acute myocarditis. MethodsEighteen healthy volunteers and 28 patients with suspected myocarditis underwent conventional 2D T1 and T2 mapping with whole heart coverage and 3D joint T1/T2 mapping on a 1.5T scanner. Acquisition time, image quality, and diagnostic performance were compared. Qualitative analysis was performed using a 4-point Likert scale. Bland-Altman plots were used to assess the quantitative agreement between 2D and 3D sequences. ResultsThe 3D T1/T2 sequence was acquired in 8mins 26s under free breathing, whereas 2D T1 and T2 sequences were acquired with breath holds in 11mins 44s (p=0.0001). All 2D images were diagnostic. For 3D images, 89% of T1 and 96% of T2 images were diagnostic with no significant difference in the proportion of diagnostic images for the 3D and 2D T1 (p=0.2482) and T2 maps (p=1.0000). Systematic bias in T1 was noted with biases of 102ms, 115ms, and 152ms for basal-apical segments, with a larger bias for higher T1 values. Good agreement between T2 values for 3D and 2D techniques was found (bias of 1.8ms, 3.9ms, and 3.6ms for basal-apical segments). The sensitivity and specificity of the 3D sequence for diagnosing acute myocarditis was 74% (95% confidence interval [CI] 49-91%) and 83% (36-100%) respectively, with an estimated c-statistic (95% CI) of 0.85 (0.79-0.91) and no statistically significant difference between the 2D and 3D sequences for the detection of acute myocarditis for T1 (p=0.2207) or T2 (p=1.0000). ConclusionFree-breathing whole heart 3D joint T1/T2 mapping was comparable to 2D mapping sequences with respect to diagnostic performance, but with the added advantages of free-breathing, and shorter scan times. Further work is required to address the bias noted at high T1 values, but this did not significantly impact on diagnostic accuracy.

A secure scheme based on polar-coded and 3D mixed domain scrambling in W-band MMW-RoF system

With the development of 6G network, the issue of physical layer security in optical fiber communication is becoming more and more significant. In this paper, a polar-coded encryption and 3D mixed domain scrambling secure scheme in W-band millimeter-wave radio-over-fiber (MMW-RoF) system is proposed. The keys are divided into the shared key and the dynamic key, and the shared key is used for constellation-level encryption and 3D mixed domain scrambling with 3D cat mapping, the dynamic key is used for polar code encryption. After RoF system transmission, the scheme can achieve a large key space of 10453, which is powerful enough to resist brute-force. Because the key is randomly selected in the codebook, this encryption scheme has the effect of resisting chosen-plaintext attacks. In terms of reliability, compared to traditional polar-OFDM and 3D QAM polar-OFDM, this scheme can achieve ∼0.4 dB and ∼0.45 dB gains in receiver sensitivity, respectively. So, the proposed scheme has good security performance and reliability performance, which has a significant potential for application in future optical networks.

Editorial on Special Issue “3D Reconstruction and Mobile Mapping in Urban Environments Using Remote Sensing”

Both 3D reconstruction and mobile mapping are critical in supporting various applications in urban environments, including but not limited to autonomous driving, smart logistics, pedestrian navigation, and virtual reality [...]

Microstructure and stress mapping in 3D at industrially relevant degrees of plastic deformation

Strength, ductility, and failure properties of metals are tailored by plastic deformation routes. Predicting these properties requires modeling of the structural dynamics and stress evolution taking place on several length scales. Progress has been hampered by a lack of representative 3D experimental data at industrially relevant degrees of deformation. We present an X-ray imaging based 3D mapping of an aluminum polycrystal deformed to the ultimate tensile strength (32% elongation). The extensive dataset reveals significant intra-grain stress variations (36 MPa) up to at least half of the inter-grain variations (76 MPa), which are dominated by grain orientation effects. Local intra-grain stress concentrations are candidates for damage nucleation. Such data are important for models of structure-property relations and damage.

A direct comparison of multi-energy x-ray and proton CT for imaging and relative stopping power estimation of plastic and ex-vivo phantoms

Objective.Proton therapy administers a highly conformal dose to the tumour region, necessitating accurate prediction of the patient's 3D map of proton relative stopping power (RSP) compared to water. This remains challenging due to inaccuracies inherent in single-energy computed tomography (SECT) calibration. Recent advancements in spectral x-ray CT (xCT) and proton CT (pCT) have shown improved RSP estimation compared to traditional SECT methods. This study aims to provide the first comparison of the imaging and RSP estimation performance among dual-energy CT (DECT) and photon-counting CT (PCCT) scanners, and a pCT system prototype.Approach.Two phantoms were scanned with the three systems for their performance characterisation: a plastic phantom, filled with water and containing four plastic inserts and a wood insert, and a heterogeneous biological phantom, containing a formalin-stabilised bovine specimen. RSP maps were generated by converting CT numbers to RSP using a calibration based on low- and high-energy xCT images, while pCT utilised a distance-driven filtered back projection algorithm for RSP reconstruction. Spatial resolution, noise, and RSP accuracy were compared across the resulting images.Main results.All three systems exhibited similar spatial resolution of around 0.54 lp/mm for the plastic phantom. The PCCT images were less noisy than the DECT images at the same dose level. The lowest mean absolute percentage error (MAPE) of RSP,(0.28±0.07)%, was obtained with the pCT system, compared to MAPE values of(0.51±0.08)%and(0.80±0.08)%for the DECT- and PCCT-based methods, respectively. For the biological phantom, the xCT-based methods resulted in higher RSP values in most of the voxels compared to pCT.Significance.The pCT system yielded the most accurate estimation of RSP values for the plastic materials, and was thus used to benchmark the xCT calibration performance on the biological phantom. This study underlined the potential benefits and constraints of utilising such a novelex-vivophantom for inter-centre surveys in future.

Open-set 3D semantic instance maps for vision language navigation – O3D-SIM

Humans excel at forming mental maps of their surroundings, equipping them to understand object relationships and navigate based on language queries. Our previous work SI Maps (Nanwani L, Agarwal A, Jain K, et al. Instance-level semantic maps for vision language navigation. In: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE; 2023 Aug.) showed that having instance-level information and the semantic understanding of an environment helps significantly improve performance for language-guided tasks. We extend this instance-level approach to 3D while increasing the pipeline's robustness and improving quantitative and qualitative results. Our method leverages foundational models for object recognition, image segmentation, and feature extraction. We propose a representation that results in a 3D point cloud map with instance-level embeddings, which bring in the semantic understanding that natural language commands can query. Quantitatively, the work improves upon the success rate of language-guided tasks. At the same time, we qualitatively observe the ability to identify instances more clearly and leverage the foundational models and language and image-aligned embeddings to identify objects that, otherwise, a closed-set approach wouldn't be able to identify. Project Page - https://smart-wheelchair-rrc.github.io/o3d-sim-webpage

Towards automatic urban tree inventory: Enhancing tree instance segmentation via moving object removal and a chord length-based DBH estimation approach

To enhance urban forestry efficacy in Hong Kong, implementing a paradigm shift towards an automated urban tree inventory that utilizes advanced sensing technologies and artificial intelligence is essential for streamlined data collection and analysis. This study advances this objective by creating a comprehensive framework for estimating diameter at breast height (DBH) and extracting tree images. This framework encompasses five key stages: (1) data acquisition utilizing StructXray, a mobile mapping system equipped with a 360° camera and a multi-beam flash LiDAR sensor; (2) vegetation point clouds extraction using deep learning techniques; (3) individual tree segmentation through machine learning algorithms; (4) DBH estimation; and (5) tree image extraction. Six datasets were collected, yielding tree detection precision, recall and F1 score of 0.88, 0.95 and 0.91 respectively. The presence of moving objects within the 3D point cloud map, exhibiting diverse geometric structures, hinders precise vegetation point cloud segmentation by the pointwise neural network. To tackle this challenge, SalsaNext was employed to rectify the predictions of a pointwise neural network, specifically RandLA-Net in this study, eliminating 91 % of misclassified moving object point clouds and completely removing them from 47 % of affected individual tree point clouds. Additionally, a chord length-based method was proposed to enhance DBH estimation accuracy by dividing the point cloud slice into sectors and summing the chord lengths to estimate the tree trunk perimeter. Compared to the ellipse least squares fitting method, this approach reduced the root-mean-square error of the estimated DBH by 1.31 cm.

The Lyα Nondetection by JWST NIRSpec of a Strong Lyα Emitter at z = 5.66 Confirmed by MUSE

The detections of Lyα emission in galaxies with redshifts above 5 are of utmost importance for constraining the cosmic reionization timeline, yet such detections are usually based on slit spectroscopy. Here we investigate the significant bias induced by slit placement on the estimate of Lyα escape fraction ( fescLyα ) by presenting a galaxy (dubbed A2744-z6Lya) at z = 5.66, where its deep JWST/NIRSpec prism spectroscopy completely misses the strong Lyα emission detected in the MUSE data. A2744-z6Lya exhibits a pronounced UV continuum with an extremely steep spectral slope of β=−2.640−0.008+0.008 , and it has a stellar mass of ∼108.75 M ⊙, a star formation rate of ∼5.95 M ⊙ yr−1, and a gas-phase metallicity of 12+log(O/H)∼7.90 . The observed flux and rest-frame equivalent width of its Lyα from MUSE spectroscopy are 1.2 × 10−16 erg s−1 cm−2 and 75 Å, equivalent to fescLyα=42%±1% . However, its Lyα nondetection from JWST NIRSpec gives a 5σ upper limit of <5%, in stark contrast to that derived from MUSE. To explore the reasons for this bias, we perform spatially resolved stellar population analysis of A2744-z6Lya using the JWST NIRCam and HST imaging data to construct 2D maps of star formation rate, dust extinction, and neutral hydrogen column density. We find that the absence of Lyα in the slit regions probably stems from both the resonance scattering effect of neutral hydrogen and dust extinction. Through analyzing an extreme case in detail, this work highlights the important caveat of inferring fescLyα from slit spectroscopy, particularly when using the JWST multiplexed NIRSpec microshutter assembly.

Facile One Pot Synthesis of Hybrid Core-Shell Silica-Based Sensors for Live Imaging of Dissolved Oxygen and Hypoxia Mapping in 3D Cell Models.

Fluorescence imaging allows for noninvasively visualizing and measuring key physiological parameters like pH and dissolved oxygen. In our work, we created two ratiometric fluorescent microsensors designed for accurately tracking dissolved oxygen levels in 3D cell cultures. We developed a simple and cost-effective method to produce hybrid core-shell silica microparticles that are biocompatible and versatile. These sensors incorporate oxygen-sensitive probes (Ru(dpp) or PtOEP) and reference dyes (RBITC or A647 NHS-Ester). SEM analysis confirmed the efficient loading and distribution of the sensing dye on the outer shell. Fluorimetric and CLSM tests demonstrated the sensors' reversibility and high sensitivity to oxygen, even when integrated into 3D scaffolds. Aging and bleaching experiments validated the stability of our hybrid core-shell silica microsensors for 3D monitoring. The Ru(dpp)-RBITC microparticles showed the most promising performance, especially in a pancreatic cancer model using alginate microgels. By employing computational segmentation, we generated 3D oxygen maps during live cell imaging, revealing oxygen gradients in the extracellular matrix and indicating a significant decrease in oxygen level characteristics of solid tumors. Notably, after 12 h, the oxygen concentration dropped to a hypoxic level of PO2 2.7 ± 0.1%.

A systematic literature review of low-cost 3D mapping solutions

In "low-cost" solutions, ensuring economic accessibility and democratizing the availability of emerging technologies stand as pivotal considerations. This study undertakes a systematic literature review of low-cost 3D mapping solutions. Leveraging SCOPUS as the primary database, a comprehensive bibliometric analysis encompassing 1380 publications was conducted, subsequently narrowing the focus to 87 recent publications for detailed review. This research endeavors to delineate the defining characteristics of low-cost systems, elucidate their principal applications and preferred platforms, assess accessibility level, gauge the extent of innovation in both hardware and software development, explore the contributions of Deep Learning and data fusion, evaluate the consideration of data quality, and examine the contemporary relevance of photogrammetry within low-cost context. The findings demonstrate that many authors subjectively use the term low-cost to highlight qualities of a technology, methodology or sensor, but challenges arise from data quality comparisons with high-cost systems.