Coherent Point Research Articles

Non-contact tracking of shoulder bones using ultrasound and stereophotogrammetry

PurposeWe explored the integration of 3D ultrasound (US) imaging with motion capture technology for non-invasively tracking bones of the shoulder district during normal activity. Our study aimed to demonstrate ex-vivo the proposed 3D US method’s feasibility and accuracy of tracking shoulder bones in a controlled cadaveric shoulder positioned in various arm elevations (low, mid and high).MethodWe registered previously acquired full bone shapes to spatially small bony surface patches segmented from 3D US. The bone registration approach used was based on in silico analyses that investigated the effects of different — 1) registration algorithms (Iterative-Closest-Point–ICP, and Coherent Point Drift–CPD) and 2) initial estimate levels of the bone model pose relative to the targeted final bone pose—on the overall registration efficiency and accuracy in a controlled environment.ResultsCPD provided the highest accuracy in the simulation at the cost of 8x longer computation compared to ICP. The RMSE errors were <1 mm for the humerus and scapula at all elevations. Ex-vivo, the CPD registration errors were (Humerus = 2 mm and Scapula = 13.9 mm) (Humerus = 7.2 mm and Scapula = 16.8 mm) and (Humerus = 14.28 mm and Scapula = 27.5 mm), for low, medium and high elevations respectively.ConclusionIn summary, we demonstrated the feasibility and accuracy of tracking shoulder bones with 3D US in a simulation and a cadaveric experiment. We discovered that CPD may be a more suitable registration method for the task than ICP. We also discussed that 3D US with motion capture technology is very promising for dynamic bone tracking, but the US technology may not be ready for the task yet.

Fusing LiDAR and Photogrammetry for Accurate 3D Data: A Hybrid Approach

The fusion of LiDAR and photogrammetry point clouds is a necessary advancement in 3D-modeling, enabling more comprehensive and accurate representations of physical environments. The main contribution of this paper is the development of an innovative fusion system that combines classical algorithms, such as Structure from Motion (SfM), with advanced machine learning techniques, like Coherent Point Drift (CPD) and Feature-Metric Registration (FMR), to improve point cloud alignment and fusion. Experimental results, using a custom dataset of real-world scenes, demonstrate that the hybrid fusion method achieves an average error of less than 5% in the measurements of small reconstructed objects, with large objects showing less than 2% deviation from real sizes. The fusion process significantly improved structural continuity, reducing artifacts like edge misalignments. The k-nearest neighbors (kNN) analysis showed high reconstruction accuracy for the hybrid approach, demonstrating that the hybrid fusion system, particularly when combining machine learning-based refinement with traditional alignment methods, provides a notable advancement in both geometric accuracy and computational efficiency for real-time 3D-modeling applications.

Towards H&E Referenced Multiplex Immunofluorescence Interpretation: Spatial Co-localization, Cell Feature Validation, and Virtual H&E Generation.

Multiplexed Immunofluorescence (MxIF) enables detailed immune cell phenotyping, providing critical insights into cell behavior within the tumor immune microenvironment (TIME). However, signal integrity can be compromised due to the complex cyclic staining processes inherent to MxIF. Hematoxylin and Eosin (H&E) staining, on the other hand, offers complementary information through its depiction of cell morphology and texture patterns and is often visually cross-referenced with MxIF in clinical settings. In this study, we proposed a novel framework to align H&E and MxIF images for precise cross-modal cell feature validation. Using cell detection outputs from each modality as anchors, we formulated the multimodal image registration problem as point set alignment. Coherent Point Drift (CPD) is employed for initial alignment, followed by Graph Matching (GM) for refinement. Evaluations on ovarian cancer tissue microarrays (TMAs) demonstrate that our method achieves high alignment accuracy, enabling reliable validation of cell-level features across modalities for both restained and serial sections. Our results indicate that restained H&E enhances confidence in findings derived from MxIF. Additionally, we demonstrated the feasibility of generating high-quality virtual H&E images from MxIF data when restained H&E is unavailable, offering a viable alternative for integrated multimodal analysis.

Evaluating the stability of architectural heritage from the perspective of InSAR: a practical study on Jianchuan Ancient Town

The increase in human activities and natural degradation often leads to tilting, collapsing, and other forms of deterioration in architectural heritage, posing significant threats to its safety. Therefore, timely detection of abnormal deformation signals in buildings is essential for the protection of architectural heritage. Spaceborne synthetic aperture radar interferometry (InSAR) can detect slight displacements over large areas. However, relying solely on annual mean velocity maps derived from InSAR may not accurately assess the stability of ancient buildings. In this study, we developed a framework that evaluates the stability of individual buildings by integrating the InSAR displacements with building footprints. Vertical and rotational deformations, along with the temporal evolution of these deformations, are combined to generate the results for building stability assessment. We used 74 TerraSAR-X images captured from August 2017 to November 2019 to evaluate the stability of Jianchuan Ancient Town, a renowned National Historical and Cultural City in China. The displacement result suggests that the majority of Jianchuan Ancient Town remains stable, with over 93% of coherent points (CTs) displaying displacement velocities ranging from −5 to 5 mm/yr. Out of the 1,891 buildings in Jianchuan Ancient Town, 1404 are considered stable, 352 are of moderate stability, and 12 are deemed unstable. This study showed the potential of InSAR applications in assessing the stability of architectural heritages, emphasizing its crucial role in heritage preservation and management.

Detection service based on coherent point cloud analysis with AI methods using CENAGIS libraries

Detection service based on coherent point cloud analysis with AI methods using CENAGIS libraries

Photometric, astrometric, and kinematical characteristics of two Xuyi’s open clusters utilizing Gaia DR3 data

This study reports and examines two poorly studied open star clusters surveyed from XSTPS-GAC, namely Xuyi 15 and Xuyi 23, using the Gaia DR3 catalog data. We identified 570 (Xuyi 15) and 824 (Xuyi 23) stars as highly probable astrometric members with membership probability higher than 60%. By fitting King’s profile on radial density profiles (RDPs), we estimated both core and limiting radii and found rc about 1.95 ± 0.07 (Xuyi 15) and 4.55 ± 0.47 (Xuyi 23) while rlim are about 8.55 ± 2.92 (Xuyi 15) and 16.56 ± 4.07 (Xuyi 23) in pc units. We constructed CMDs for both clusters and calculated the fundamental parameters using the best-fitted isochrones of metallicity Z=0.03 and log age (yr) = 9.0 ± 0.05. The heliocentric distances are determined to be 7.413±0.90 kpc and 6.223±0.80 kpc for the clusters Xuyi 15 and Xuyi 23, respectively, using the isochrone fitting method. We have also obtained distances as 7.05-0.25+0.65 and 6.90-0.30+0.72 kpc for both clusters using the Bailer-Jones method. Moreover, total mass (MC;M⊙) was deduced with mass-luminosity relation (MLR) as 684 ± 26 and 1158 ± 34 and luminosity function (LF) concluded the absolute (MG; mag) of 4.05 ± 0.05 and 3.42 ± 0.04 for Xuyi 15 and Xuyi 23 clusters respectively. The overall mass function reflects the slopes (α) for Salpeter’s value (2.35) within the uncertainty (i.e., αXuyi15 = 2.52 ± 0.06 and αXuyi23 = 2.34 ± 0.05). The present study and the dynamical analysis for different evolving times demonstrate that the clusters are dynamically relaxed, where the dynamical evolution parameter (τ) is much greater than one. Finally, we computed their coherent convergent points with AD-diagram method, thus (Ao,Do) are (99o.27 ± 0o.11, 20o.91 ± 0o.22; Xuyi 15) and (123o.34 ± 0o.09, -58o.27 ± 0o.13; Xuyi 23).

Research on registration method for enface image using multi-feature fusion

Objective.The purpose of this work is to accurately and quickly register the Optical coherence tomography (OCT) projection (enface) images at adjacent time points, and to solve the problem of interference caused by CNV lesions on the registration features.Approach.In this work, a multi-feature registration strategy was proposed, in which a combined feature (com-feature) containing 3D information, intersection information and SURF feature was designed. Firstly, the coordinates of all feature points were extracted as combined features, and then these feature coordinates were added to the initial vascular coordinate set simplified by the Douglas-Peucker algorithm as the point set for registration. Finally, the coherent point drift registration algorithm was used to register the enface coordinate point sets of adjacent time series.Main results.The newly designed features significantly improve the success rate of global registration of vascular networks in enface images, while the simplification step greatly improves the registration speed on the basis of preserving vascular features. The MSE, DSC and time complexity of the proposed method are 0.07993, 0.9693 and 42.7016 s, respectively.Significance.CNV is a serious retinal disease in ophthalmology. The registration of OCT enface images at adjacent time points can timely monitor the progress of the disease and assist doctors in making diagnoses. The proposed method not only improves the accuracy of OCT enface image registration, but also significantly reduces the time complexity. It has good registration results in clinical routine and provides a more efficient method for clinical diagnosis and treatment.

Lensing Point-spread Function of Coherent Astrophysical Sources and Nontrivial Wave Effects

Most research on astrophysical lensing has been conducted using the geometric optics framework, where there exists a clear concept of lensing images. However, wave optics effects can be important for coherent sources, e.g., pulsars, fast radio bursts, and gravitational waves observed at long wavelengths. There, the concept of lensing images needs an extension. We introduce the concept of the “lensing point-spread function” (LPSF), the smoothed flux density distribution of a coherent point source after being lensed, as a generalization of the lensing image concept at finite frequencies. The frequency-dependent LPSF captures the gradual change of the flux density distribution of the source from discrete geometric images at high frequencies to a smooth distribution at low frequencies. It complements other generalizations of lensing images, notably the imaginary images and the Lefschetz thimbles. Being a footprint of a lensing system, the LPSF is useful for theoretical studies of lensing. Using the LPSF, we identify a frequency range with nontrivial wave effects, where both geometric optics and perturbative wave optics fail, and determine this range to be ∣κ∣−1 ≲ ν ≲ 10, with κ and ν being the dimensionless lens amplitude and the reduced observing frequency, respectively. Observation of LPSFs with nontrivial wave effects requires either very close-by lenses or very large observing wavelengths. The potential possibilities are the lensing of gravitational waves, the plasma lensing of Milky Way pulsars, and lensing by the solar gravitational lens.

An improved time series SAR interferometry (TSInSAR) for investigating earthquake-induced active unstable slopes (AUS) in Pakistan

ABSTRACT Time series interferometric SAR (TSInSAR) techniques face challenges related to the availability of highly coherent point targets in non-urban, vegetated, and mountainous regions. In this study, we tested an improved TSInSAR approach with the help of distributed scatterers (DS) detected through the fast statistically homogeneous pixel selection (faSHP) approach and jointly processed with persistent scatterers (PS) within the interferometric point target analysis (IPTA) framework. The method is applied to a seismically active and highly gradient terrain to investigate the earthquake-induced active unstable slopes (AUS) in the Muzaffarabad-Balakot region of northern Pakistan, particularly using sixteen PALSAR-2 images acquired between October 2014 and May 2020. However, its effectiveness was also assessed by using Sentinel-1 data from the same time period. The quantitative assessment showed the effectiveness of the method in delineating the sliding surfaces of the unstable slopes and achieving approximately four times higher point density as compared to the standard PSI approach when applied to PALSAR-2 data and approximately nine times higher point targets when Sentinel-1 data is used. Exhibiting an average deformation rate varying between −40 mm yr−1 and 20 mm yr−1 along the line of sight (LOS) direction, the obtained results from PALSAR-2 data revealed the existence of 451 AUS in the region. The study also reports the discovery of a giant destabilized slope (~2.30 sq. km) located near Patika Village along the Neelam River. The majority of these unstable slopes are found at altitudes above 780 m, with slope angles ranging from 15 to 50 degrees. The study also found a significant correlation between deformation patterns and local precipitation. The rainwater gradually penetrates into the joints and cracks, accelerating the processes of deformation and slope failure. The research and its findings could help decision-making entities by providing first-hand information for managing the risks associated with slope failure.

Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift

Background and ObjectiveRegistration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues. MethodsTo overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points. ResultsThis study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances <2 and 8 mm, respectively, and a mean and a maximum target registration error <2 mm and 5 mm on both internal and external validation datasets. The paired two-sample t-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (p < 0.05). ConclusionsThe proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.

Extraordinary optical characteristics in a one-dimensional parity-time symmetric structure of quasiperiodic two-material Octonacci optical waveguide network

We explore Exceptional Points (EPs) within a one-dimensional quasiperiodic Octonacci optical waveguide network. This network consists of segments, each composed of two-material subsegments featuring gain and loss materials, creating a parity-time-symmetric structure. We investigate the trend of EPs across generations 3 to 7 of the Octonacci sequence using the generalized eigenfunction method and transfer matrix method. Our findings reveal that as generations progress, band gaps become more pronounced, and the number of EPs significantly increases within these gaps. In particular, the third generation only supports unidirectional transparency. Bidirectional transparency appears in the fourth generation and becomes more pronounced in later generations. Coherent perfect absorption-lasing points are first seen in the seventh generation. These findings have implications for the design of all-optical devices and wideband and/or narrowband optical filters.

Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept

Background and aim3D fusion model of cone-beam computed tomography (CBCT) and oral scanned data can be used for the accurate design of root canal access and guide plates in root canal therapy (RCT). However, the pose accuracy of the dental pulp and crown in data registration has not been investigated, which affects the precise implementation of clinical planning goals. We aimed to establish a novel registration method based on pulp horn mapping surface (PHMSR), to evaluate the accuracy of PHMSR versus traditional methods for crown-pulp registration of CBCT and oral scan data.Materials and methodsThis vitro study collected 8 groups of oral scanned and CBCT data in which the left mandibular teeth were not missing, No. 35 and No. 36 teeth were selected as the target teeth. The CBCT and scanned model were processed to generate equivalent point clouds. For the PHMSR method, the similarity between the feature directions of the pulp horn and the surface normal vectors of the crown were used to determine the mapping points in the CBCT point cloud that have a great influence on the pulp pose. The small surface with adjustable parameters is reconstructed near the mapping point of the crown, and the new matching point pairs between the point and the mapping surface are searched. The sparse iterative closest point (ICP) algorithm is used to solve the new matching point pairs. Then, in the C + + programming environment with a point cloud library (PCL), the PHMSR, the traditional sparse ICP, ICP, and coherent point drift (CPD) algorithms are used to register the point clouds under two different initial deviations. The root square mean error (RSME) of the crown, crown-pulp orientation deviation (CPOD), and position deviation (CPPD) were calculated to evaluate the registration accuracy. The significance between the groups was tested by a two-tailed paired t-test (p < 0.05).ResultsThe crown RSME values of the sparse ICP method (0.257), the ICP method (0.217), and the CPD method (0.209) were not significantly different from the PHMSR method (0.250). The CPOD and CPPD values of the sparse ICP method (4.089 and 0.133), the ICP method (1.787 and 0.700), and the CPD method (1.665 and 0.718) than for the PHMSR method, which suggests that the accuracy of crown-pulp registration is higher with the PHMSR method.ConclusionCompared with the traditional method, the PHMSR method has a smaller crown-pulp registration accuracy and a clinically acceptable deviation range, these results support the use of PHMSR method instead of the traditional method for clinical planning of root canal therapy.

Coupling Coherent Point Drift And Affine Least-Squares Transformation To Build Trajectories In TR-PTV

The robustness and accuracy of state-of-the-art time-resolved Particle Tracking Velocimetry algorithms is strongly supported by the use of the temporal coherence of particle trajectories. However, to exploit this coherence, the particle needs to be tracked for a sufficiently long period. This condition cannot be achieved if the time of flight of the particles across the measurement volume is not long enough, for example because the limited illumination energy requires the thickness of the volume to be thin. The authors propose to address this difficulty by providing an algorithm based on the spatial coherence of the trajectories rather than the temporal one. This algorithm results from the coupling of two methods; the Coherent Point Drift (CPD), which has proven to be accurate in pairing particles from two instants, but with an insufficient recall for time-resolved application, and the Affine Least Square Transformation (ALST), which allows transporting particles that were missed by the CPD. This algorithm is integrated into a global process that includes an Iterative Particle Reconstruction (IPR) algorithm to extract a list of particles from the images. First tests performed on a synthetic test case consisting of images of particles advected by a turbulent flow highlighted the potential of the method for tracking short tracks. With six frames, the recall is found to be 99.6% with the present method against 98.3% with the DaVis 10.2 implementation of ShakeThe-Box (STB). However, the error is much larger with a false positive rate of 5.1% with our method but only 0.2% with (STB). The cause of this high error rate is analysed and it is speculated that it is partly explained by the tendency of the IPR to detect the same real particle multiple times, which is a concern that has to be addressed in future work.

A Particle Based Approach For Improved Resolution PIV And TOMO-PIV Based On The Coherent Point Drift And The Affine Least-Squares Transformation

Particle Image Velocimetry (PIV) is a widely used method for flow diagnostics, but there is still potential for improvement, particularly in terms of velocity gradient estimation and computational cost when considering three-dimensional problems. This paper presents a framework that combines a Particle Tracking Velocity (PTV) approach with local gradient-based Eulerian reconstruction to improve PIV performance. The approach uses the Coherent Point Drift (CPD) method for particle pairing and introduces the Affine Least-Squares Transformation (ALST) for local deformation gradient estimation. The CPD method consists of pairing particles whose positions at two successive instants have been obtained from the images. The ALST estimates local deformation gradients, allowing the Eularian reconstruction of the velocity field. The effectiveness of the proposed method compared to traditional PIV algorithms is demonstrated by synthetic test cases in both 2D and 3D configurations. In 2D cases, the CPD+ALST approach outperforms standard PIV methods, especially in capturing local velocity gradients. In 3D cases, comparisons with TOMO-PIV show the improved performance of CPD+ALST in the context of locally large velocity gradients. However, the linear nature of ALST makes it less efficient than quadratic binning techniques. The study demonstrates the potential of CPD+ALST to improve velocity field reconstruction in complex flows.

Distributed fiber optic sensing based on multipath data compression fusion

In conventional distributed sensing systems, the sampling rate exceeds the requisite sampling rate for system spatial resolution due to direct sampling of electrical signals. Furthermore, unrelated sensing paths exhibit distinct coherent fading points. Through the application of sampling point compression and multipath fusion, this study effectively resolves issues such as coherent fading and low signal-to-noise ratio (SNR) commonly encountered in single-path distributed sensing systems. In the initial stage, within two independent single-mode optical fiber structures, a consistent rotation of data along different fiber paths is performed. Subsequently, a segmentation compression and fusion method is applied. Experimental results demonstrate effective suppression of coherent fading along the sensing paths, an improvement of 9 dB in SNR, unaffected spatial resolution, and a significant reduction in data processing load for subsequent processing modules. This method can be widely applied in distributed sensing systems that allow for multipath division.

Symmetry of the left and right tibial plafond; a comparison of 75 distal tibia pairs.

Tibia plafond or pilon fractures present a high level of complexity, making their surgical management challenging. Three-Dimensional Virtual Planning (3DVP) can assist in preoperative planning to achieve optimal fracture reduction. This study aimed to assess the symmetry of the left and right tibial plafond and whether left-right mirroring can reliably be used. Bilateral CT scans of the lower limbs of 75 patients without ankle problems or prior fractures of the lower limb were included. The CT images were segmented to create 3D surface models of the tibia. Subsequently, the left tibial models were mirrored and superimposed onto the right tibia models using a Coherent Point Drift surface matching algorithm. The tibias were then cut to create bone models of the distal tibia with a height of 30mm, and correspondence points were established. The Euclidean distance was calculated between correspondence points and visualized in a boxplot and heatmaps. The articulating surface was selected as a region of interest. The median left-right difference was 0.57mm (IQR, 0.38 - 0.85mm) of the entire tibial plafond and 0.53mm (IQR, 0.37 - 0.76mm) of the articulating surface. The area with the greatest left-right differences were the medial malleoli and the anterior tubercle of the tibial plafond. The tibial plafond exhibits a high degree of bilateral symmetry. Therefore, the mirrored unfractured tibial plafond may be used as a template to optimize preoperative surgical reduction using 3DVP techniques in patients with pilon fractures.

Coherent point drift with Skewed Distribution for accurate point cloud registration

Point cloud registration methods based on Gaussian Mixture Models (GMMs) exhibit high robustness. However, GMM cannot precisely depict point clouds, because the Gaussian distribution is spatially symmetric and local surfaces of point clouds are typically non-symmetric. In this paper, we propose a novel method for rigid point cloud registration, termed coherent point drift with Skewed Distribution (Skewed CPD). Our method employs an asymmetric distribution constructed from the local surface normals and curvature radii. Compared to the Gaussian distribution, this skewed distribution provides a more accurate spatial description of points on local surfaces. Additionally, we integrate an adaptive multiplier to the covariance, which reallocates the weight of the covariance for different components in the probabilistic mixture model. We employ the EM algorithm to address this maximum likelihood estimation (MLE) issue and leverage GPU acceleration. In the M-step, we adopt an unconstrained optimization technique rooted in a Lie group and Lie algebra to attain the optimal transformation. Experimental results indicate that our method outperforms state-of-the-art methods in both accuracy and robustness. Remarkably, even without loop closure detection, the cumulative error of our approach remains minimal.

Unveiling interactions between intervertebral disc morphologies and mechanical behavior through personalized finite element modeling.

Introduction: Intervertebral Disc (IVD) Degeneration (IDD) is a significant health concern, potentially influenced by mechanotransduction. However, the relationship between the IVD phenotypes and mechanical behavior has not been thoroughly explored in local morphologies where IDD originates. This work unveils the interplays among morphological and mechanical features potentially relevant to IDD through Abaqus UMAT simulations. Methods: A groundbreaking automated method is introduced to transform a calibrated, structured IVD finite element (FE) model into 169 patient-personalized (PP) models through a mesh morphing process. Our approach accurately replicates the real shapes of the patient's Annulus Fibrosus (AF) and Nucleus Pulposus (NP) while maintaining the same topology for all models. Using segmented magnetic resonance images from the former project MySpine, 169 models with structured hexahedral meshes were created employing the Bayesian Coherent Point Drift++ technique, generating a unique cohort of PP FE models under the Disc4All initiative. Machine learning methods, including Linear Regression, Support Vector Regression, and eXtreme Gradient Boosting Regression, were used to explore correlations between IVD morphology and mechanics. Results: We achieved PP models with AF and NP similarity scores of 92.06\% and 92.10\% compared to the segmented images. The models maintained good quality and integrity of the mesh. The cartilage endplate (CEP) shape was represented at the IVD-vertebra interfaces, ensuring personalized meshes. Validation of the constitutive model against literature data showed a minor relative error of 5.20%. Discussion: Analysis revealed the influential impact of local morphologies on indirect mechanotransduction responses, highlighting the roles of heights, sagittal areas, and volumes. While the maximum principal stress was influenced by morphologies such as heights, the disc's ellipticity influenced the minimum principal stress. Results suggest the CEPs are not influenced by their local morphologies but by those of the AF and NP. The generated free-access repository of individual disc characteristics is anticipated to be a valuable resource for the scientific community with a broad application spectrum.

A temporary soil dump settlement and landslide risk analysis using the improved small baseline subset-InSAR and continuous medium model

Abandoned soil disposal in China has become increasingly challenging, which may pose significant safety hazards such as soil settlement and landslides. Interferometry Synthetic Aperture Radar (InSAR) is effective in surface deformation monitoring and Small Baseline Subset-InSAR (SBAS-InSAR) can obtain sufficient coherent point density from the bare soil surface. This study investigated Chishi soil dump in the Shenzhen-Shanwei Special Cooperation Zone (SSSCZ), and a total of 91 Sentinel-1 images from 2019 to 2022 was processed. Accordingly, an improved SBAS-InSAR method was utilized to analyze the soil dump’s time-series deformation, and multi-source remote sensing data were used for auxiliary interpretation. Our results indicate that precipitation, high temperature, and construction vibrations may cause instability of the soil dump. Therefore, a depth-integrated continuous medium model was introduced to analyze the potential landslide risk of the soil dump, which demonstrate that a landslide will likely occur, harm personnel, and damage the buildings surrounding the Chishi soil dump when it was saturated (λ ≥ 0.50). This research can provide a vital case reference for the analysis, interpretation, disaster prevention, and control evaluation of similar soil dumps.

A robust pairing method for two-pulse particle tracking velocimetry based on coherent point drift

Particle tracking velocity has reached a high level of maturity in time-resolved measurements since the introduction and development of the Shake-The-Box algorithm. The effectiveness of this approach lies, in part, in its ability to exploit the temporal coherence of particle trajectories to reject the ghost particles while increasing the density of true particles. However, certain situations may prevent time-resolved measurements. In those cases, a Two-Pulse configuration is often the only option. This raises a challenge with regard to the capacity in separating the ghost from the true particles due to the lack of long-term trajectories. This article proposes a new approach to solve this problem using the coherent point drift (CPD) method. This method identifies a spatially coherent deformation field that models the transformation between two correlated sets of points. In the context of particle tracking velocimetry, the imposed spatial coherence of this calculation is believed to act in the same way as the temporal coherence that made Shake-The-Box successful. The CPD is governed by three parameters whose optimal values have been evaluated in the present contribution. These values were found to be weakly sensitive to the characteristics of the flow under study, ensuring that this method is robust without further tuning of the parameters. The method is then compared with the Two-Pulse implementation of Shake-The-Box (2P-STB) available in Davis 10.2. For this purpose, sets of realistic images were generated at two successive times for different configurations based of synthetically generated turbulent flows. The Iterative-Particle-Reconstruction in Davis 10.2 was then used to extract the list of particles to be processed by CPD. The comparison shows a better recall with 2P-STB than CPD, especially for large time intervals between frames, but an overall better rejection of ghost particles by CPD than 2P-STB, which was the expected benefit of this method.