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The tortuosity of retinal blood vessels is an important phenomenon, and it can act as a biomarker in the diagnosis of several eye diseases. The study of abnormalities in the tortuosity of retinal arteries and veins provides ophthalmologists with important information for disease diagnosis. Our study aims to compare the tortuosity relation between retinal arteries and veins by quantifying the vessels' tortuosity in the retina using 14 tortuosity measures applied to the AV-classification retinal dataset. Two feature sets are created, one for arteries and the other for veins. The comparison between the tortuosity of arteries and veins is based on a two-sample T-test statistical method, a regression analysis between the quantified tortuosity features, principal component analysis at the dataset level, and the introduction of the arteriovenous length ratios concept to compare the variations in these new ratios to see the tortuosity behavior in each image. The methods' results have shown that the tortuosity of retinal arteries and veins is similar. The result of the two-sample T-test supports the research hypothesis, as the P-value obtained was greater than 0.05. Furthermore, the regression analysis between arteries and veins features showed a high correlation ( r 2 = 89.39% and 89.11%) for arteries and veins, respectively. The study concludes that the retinal vessel type has no statistical significance in the tortuosity calculation results. [ABSTRACT FROM AUTHOR]

Retinal vessel segmentation, skeletonization, and the generation of vessel segments are considered significant steps in any automated system for measuring the vessel biomarkers of several disease diagnoses. Most of the current tortuosity quantification methods rely on precise vascular segmentation and skeletonization of the retinal vessels. Additionally, the existence of a reference dataset for accurate vessel segment images is an essential need for implementing deep learning solutions and an automated system for measuring the vessel biomarkers of several disease diagnoses, especially for optimized quantification of vessel tortuosity or accurate measurement of AV-nicking. This study aimed to present an improved method for skeletonizing and extracting the retinal vessel segments from the 504 images in the AV classification dataset. The study utilized the Six Sigma process capability index, sigma level, and yield to measure the vessels' tortuosity calculation improvement before and after optimizing the extracted vessels. As a result, the study showed that the sigma level for the vessel segment optimization improved from 2.7 to 4.39, the confirming yield improved from 88 percent to 99.77 percent, and the optimized vessel segments of the AV classification dataset retinal images are available in monochrome and colored formats. [ABSTRACT FROM AUTHOR]

Computer vision technology is moving more and more towards a three-dimensional approach, and plant phenotyping is following this trend. However, despite its potential, the complexity of the analysis of 3D representations has been the main bottleneck hindering the wider deployment of 3D plant phenotyping. In this review we provide an overview of typical steps for the processing and analysis of 3D representations of plants, to offer potential users of 3D phenotyping a first gateway into its application, and to stimulate its further development. We focus on plant phenotyping applications where the goal is to measure characteristics of single plants or crop canopies on a small scale in research settings, as opposed to large scale crop monitoring in the field. [ABSTRACT FROM AUTHOR]

This paper presents a high-speed skeletonization algorithm for detecting the skeletons of linear objects from their binary images. The primary objective of our research is to achieve rapid extraction of the skeletons from binary images while maintaining accuracy for high-speed cameras. The proposed algorithm uses edge supervision and a branch detector to efficiently search inside the object, avoiding unnecessary computation on irrelevant pixels outside the object. Additionally, our algorithm addresses the challenge of self-intersections in linear objects with a branch detection module, which detects existing intersections and initializes new searches on emerging branches when necessary. Experiments on various binary images, such as numbers, ropes, and iron wires, demonstrated the reliability, accuracy, and efficiency of our approach. We compared the performance of our method with existing skeletonization techniques, showing its superiority in terms of speed, especially for larger image sizes. [ABSTRACT FROM AUTHOR]

The paper analyses Peirce's hypoiconicity through the lens of Husserlian intentionality. Peirce's triple structure of hypoiconicity as resemblance relation, diagrammatical reasoning and metaphoric displacement is shown to require intentional acts in its production and interpretation. Regarding hypoiconicity as a semiotic schematization of Vorstellung, the paper places it in the context of Husserl's conception of intentionality in which iconicity appears as a stepping-stone towards the skeletonization of resemblance in diagrammatical abstraction and as schematic displacement in metaphor. As such, hypoiconic intentionality is argued to play a role also in Peirce's community conception of language. The paper's core claim is that intentionality provides an avenue for revealing hypoiconicity as a major, critical concept of semiotics, functioning as paradigm case for investigating the convergence of semiotics and phenomenology. [ABSTRACT FROM AUTHOR]

Character skeletonization is a critical aspect of the accurate digital analysis of ancient manuscripts. Our study introduces PrecisionGAN, a generative adversarial network (GAN) specifically tailored for the skeletonization of ancient manuscript characters, marking an advancement in cultural heritage analysis. PrecisionGAN utilizes a U-Net-based generator with innovative multi-head attention and residual connections, combined with a PatchGAN-based discriminator. It is fine-tuned with a hybrid loss function optimized to enhance accuracy and reduce artifacts, even when the training data is imperfect. Our evaluations show that this GAN not only excels in manuscript character skeletonization, achieving superior accuracy and image quality over existing methods but also demonstrates the potential for a range of image processing applications, such as underwater image restoration. Evaluated using the Gaussian similarity measure, our method outperformed the conventional techniques up to 81% of the cases. Further assessments with the structural similarity index measure and a customized metric focused on endpoints and junctions yielded comparable or superior results. This research highlights the versatility of our approach to preserving and interpreting cultural heritage through cutting-edge digital technologies. [ABSTRACT FROM AUTHOR]

Although various structural optimization techniques have a sound mathematical basis, the structural robustness and practical constructability of optimal designs pose a great challenge in the manufacturing stage. This paper presents an automated novel approach stemming from structural optimization and engineering principles, where discrete members of the structurally optimized designs are driven towards optimal utilization. The developed workflow unifies topology, layout and size optimization in a single parametric platform, which subsequently outputs a ready-to-manufacture CAD skeletal model which can be manufactured either additively or by assembly. All such outputs are checked and validated for structural requirements; strength, stiffness and stability in accordance with standard codes of practice. In the implementations, first, a topology-optimal model is generated and converted to a one-pixel-wide chain model using skeletonization. Herein, this paper uses a novel efficient method to extract the skeleton by using pixel-padding near the domain borders. Secondly, a spatial frame is extracted from the skeleton for its member size and layout optimization. Finally, the CAD model is generated using constructive solid geometry trees and the structural integrity of each member is assessed to ensure structural robustness prior to manufacturing. Various examples presented in the paper showcase the validity of the presented workflow across various structural engineering applications. • A novel method for design-informed structural optimisation is developed. • Handles both additive and assembly-based manufacturing techniques. • Optimal design outputs are structurally safe, stable and adequately-stiff. • Automated ready-to-manufacture CAD model outputs improve design efficiency. [ABSTRACT FROM AUTHOR]

Branch identification is key to the robotic pruning system for apple trees. High identification accuracy and the positioning of junction points between branch and trunk are important prerequisites for pruning with a robotic arm. Recently, with the development of deep learning, Transformer has been gradually applied to the field of computer vision and achieved good results. However, the effect of branch identification based on Transformer has not been verified so far. Taking Swin-T and Resnet50 as a backbone, this study detected and segmented the trunk, primary branch and support of apple trees on the basis of Mask R-CNN and Cascade Mask R-CNN. The results show that, when Intersection over Union (IoU) is 0.5, the bbox mAP and segm mAP of Cascade Mask R-CNN Swin-T are the highest, which are 0.943 and 0.940; as for the each category identification, Cascade Mask R-CNN Swin-T shows no significant difference with the other three algorithms in trunk and primary branch; when the identified object is a support, the bbox AP and segm AP of Cascade Mask R-CNN Swin-T is significantly higher than that of other algorithms, which are 0.879 and 0.893. Next, Cascade Mask R-CNN SW-T is combined with Zhang & Suen to obtain the junction point. Compared with the direct application of Zhang & Suen algorithm, the skeleton obtained by this method is advantaged by trunk diameter information, and its shape and junction points position are closer to the actual apple trees. This model and method can be applied to follow-up research and offer a new solution to the robotic pruning system for apple trees. [ABSTRACT FROM AUTHOR]

A fast algorithm for solving large multi-scale scattering problems by the volume–surface integral equation (VSIE) is proposed. The sub-matrices of the near-field interactions (NFIs) in terms of the multi-level fast multipole algorithm (MLFMA) are compressed by the skeletonization after the theoretical and numerical investigations on their low-rankness are carried out. A block-diagonal preconditioner (BDP) based on the recursive skeletonization (RS) is developed to improve the conditioning of the impedance matrix of the VSIE. The rules to select hyperparameters in the proposed method are given. Numerical experiments conducted on scattering problems show the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Tree skeletons play an important role in tree structure analysis and 3D model reconstruction. However, it is a challenge to extract a skeleton from a tree point cloud with complex branches. In this paper, an automatic and fast tree skeleton extraction method (FTSEM) based on voxel thinning is proposed. In this method, a wood–leaf classification algorithm was introduced to filter leaf points for the reduction of the leaf interference on tree skeleton generation, tree voxel thinning was adopted to extract a raw tree skeleton quickly, and a breakpoint connection algorithm was used to improve the skeleton connectivity and completeness. Experiments were carried out in Haidian Park, Beijing, in which 24 trees were scanned and processed to obtain tree skeletons. The graph search algorithm (GSA) was used to extract tree skeletons based on the same datasets. Compared with the GSA method, the FTSEM method obtained more complete tree skeletons. The time cost of the FTSEM method was evaluated using the runtime and time per million points (TPMP). The runtime of FTSEM was from 1.0 s to 13.0 s, and the runtime of GSA was from 6.4 s to 309.3 s. The average value of TPMP was 1.8 s for FTSEM and 22.3 s for GSA, respectively. The experimental results demonstrate that the proposed method is feasible, robust, and fast with good potential for tree skeleton extraction. [ABSTRACT FROM AUTHOR]

Background: Xylosyltransferases-I and II (XT-I and XT-II) catalyze the initial and rate limiting step of the proteoglycan (PG) biosynthesis and therefore have an import impact on the homeostasis of the extracellular matrix (ECM). The reason for the occurrence of two XT-isoforms in all higher organisms remains unknown and targeted genome-editing strategies could shed light on this issue. Methods: XT-I deficient neonatal normal human dermal fibroblasts were generated by using the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated proteins (Cas) 9 system. We analyzed if a reduced XT-I activity leads to abnormalities regarding ECM-composition, myofibroblast differentiation, cellular senescence and skeletal and cartilage tissue homeostasis. Results: We successfully introduced compound heterozygous deletions within exon 9 of the XYLT1 gene. Beside XYLT1, we detected altered gene-expression levels of further, inter alia ECM-related, genes. Our data further reveal a dramatically reduced XT-I protein activity. Abnormal myofibroblast-differentiation was demonstrated by elevated alpha-smooth muscle actin expression on both, mRNA- and protein level. In addition, wound-healing capability was slightly delayed. Furthermore, we observed an increased cellular-senescence of knockout cells and an altered expression of target genes knowing to be involved in skeletonization. Conclusion: Our data show the tremendous relevance of the XT-I isoform concerning myofibroblast-differentiation and ECM-homeostasis as well as the pathophysiology of skeletal disorders. [ABSTRACT FROM AUTHOR]

Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this field. These methods are classified into five categories according to their methodological characteristics. The overview and brief assessment of each category are provided in the corresponding chapters, respectively. We provide a comprehensive summary among the cited publications, image modalities and datasets from various aspects, which hope to reveal the pros and cons of every method, summarize its achievements and discuss the challenges and future trends. [ABSTRACT FROM AUTHOR]

A Skeleton that is extracted by a skeletonization algorithm from a binary image is useful for object description, matching, recognition and compression. The parallel thinning algorithm, one of the skeletonization algorithms is well known to have computational effciency. The main contribution of this paper is that we proposed a novel fully parallel thinning algorithm based on a comprehensive investigation of the well-known Zhang-Suen (ZS)-series algorithms and the one-pass thinning algorithm (OPTA)-series algorithms, which not only has good performance in terms of (8,4) connectivity preservation and single-pixel thickness, but also has the following qualities: it is more robust to the boundary noise than the OPTA-series algorithms and it is faster than the ZS-series algorithms in terms of thinning speed, as confirmed by the experiments presented in this paper. [ABSTRACT FROM AUTHOR]

Skeleton creation is an important phase in the character animation pipeline. However, handcrafting skeleton takes extensive labor time and domain knowledge. Automatic skeletonization provides a solution. However, most of the current approaches are far from real-time and lack the flexibility to control the skeleton complexity. In this paper, we present an efficient skeletonization method, which can be seamlessly integrated into the sketch-based modeling process in real-time. The method contains three steps: (i) local sub-skeleton extraction; (i i) sub-skeleton connection; and (i i i) global skeleton refinement. Firstly, the local skeleton is extracted from processed polygon stroke and forms a subpart along with the sub-mesh. Then, local sub-skeletons are connected according to the intersecting relationships and modeling sequence of subparts. Lastly, a global refinement method is proposed to gives users coarse-to-fine control on the connected skeleton. We demonstrate the effectiveness of our method on a variety of examples created from both novices and professionals. [Display omitted] • A real-time skeletonization algorithm for immediately constructing an animatable skeleton from user sketch. • A flexible solution for skeleton complexity control. • An easy-to-use system for creating animatable models featured by sketch-based shape modeling and automatic rigging. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the retinal blood vascular network of the retinographies of patients with different grades of diabetic retinopathy. Methods: Ninety Retinographies (MESSIDOR database) were used, with different grades of diabetic retinopathy divided into 4 groups: no retinopathy (n=23), grade one (n=20), grade two (n=20) and grade three (n=27) diabetic retinopathy. The grades of diabetic retinopathy were classified according to the number of microaneurysms, number of hemorrhages and the presence of neovascularization. The images were skeletonized and quantified by fractal methods: dimension of box-counting (Dbc) and information (Dinf). Results: The means of Dbc values of groups were around 1.25, without statistically significant difference in the dimension values between groups for whole retina. There was also no statistical difference in Dinf values between groups, whose means ranged between 1.294 ± 0.013 (group of grade 1) and 1.3 ± 0.017 (group of grade 3). The retinographies were divided into regions of equal areas. The fractal values of some retinal regions showed statistical differences, but these differences were not enough to show the sensitivity of fractal methods in identifying diabetic retinopathy. Conclusion: The fractal methods were not able to identify the different grades of diabetic retinopathy in retinographies. [ABSTRACT FROM AUTHOR]

Internal thoracic arteries (ITAs) are the gold standard conduits for coronary revascularization because of their long-term patency and anti-atherosclerotic properties. Harvesting and preparation of ITAs for revascularization is a technically demanding procedure with multiple challenges. Over the last few decades, various methods and techniques for ITAs harvesting have been introduced by different surgeons and applied in clinical practice with different results. Harvesting of ITAs in pedicled or skeletonized fashion, with electrocautery or harmonic scalpel, with open or intact pleura, with clipping the end or keeping it perfused; papaverine delivery with intraluminal injection, perivascular injection, injecting into endothoracic fascia, and papaverine topical spray are the different techniques introduced by the number of researchers. At the same time, access to the ITAs for harvesting has also been studied. Access and harvesting through median sternotomy, mini anterolateral thoracotomy, thoracoscopic, and robotic-assisted harvesting of ITAs are the different techniques used in clinical practice. However, the single standard method for harvesting and preparation of ITAs has yet to be determined. In this review article, we aimed to discuss and analyze all these techniques of harvesting and preparing ITAs with the help of literature to find the best way for ITAs harvesting and preparation for myocardial revascularization. [ABSTRACT FROM AUTHOR]

We present a method that skeletonizes the first arriving seismic refractions by machine learning and inverts them for the subsurface velocity model. In this study, first arrivals can be compressed in a low-rank sense with their skeletal features extracted by a well-trained autoencoder. Empirical experiments suggest that the autoencoder’s $1\times 1$ or $2\times 1$ latent vectors vary continuously with respect to the input seismic data. It is, therefore, reasonable to introduce a misfit functional measuring the discrepancies between the predicted and the observed data in a low-dimensional latent space. The benefit of this approach is that an elaborated autoencoding neural network not only refines intrinsic information hidden in the refractions but also improves the quality of inversion for a reliable background velocity model. Numerical tests on both synthetic and field data demonstrate the effectiveness of this method, especially in recovering the low-to-intermediate wavenumber parts of the subsurface velocity distribution. Comparisons are made with the other three relevant methods, the wave-equation travel-time (WT) inversion, the envelope inversion, and the full waveform inversion (FWI). As expected, the cycle skipping problem is alleviated due to the reduction of dimensions of data space. This method outperforms the envelope inversion in resolution, and it is no worse than WT. Moreover, there is no need for careful manual travel-time picking with this methodology. In general, this inversion framework provides an extendable strategy to compress any input data for reconstructing high-dimensional physical parameters. [ABSTRACT FROM AUTHOR]

Objectives: The advent of micro‐computed tomography (μCT) made cancellous bone more accessible than ever before. Nevertheless, the characterization of cancellous bone is made difficult by its inherent complexity and the difficulties in defining homology across datasets. Here we propose novel virtual methodological approaches to overcome those issues and complement existing methods. Materials and methods: We present a protocol for the isolation of the whole cancellous region within a μCT scanned bone. This method overcomes the subsampling issues and allows studying cancellous bone as a single unit. We test the protocol on a set of primate bones. In addition, we describe a set of morphological indices calculated on the topological skeleton of the cancellous bone: node density, node connectivity, trabecular angle, trabecular tortuosity, and fractal dimension. The usage of the indices is shown on a small comparative sample of primate femoral heads. Results: The isolation protocol proves reliable in isolating cancellous structures from several different bones, regardless of their shape. The indices seem to detect some functional differences, although further testing on comparative samples is needed to clarify their potential for the study of cancellous architecture. Conclusions: The approaches presented overcome some of the difficulties of trabecular bone studies. The methods presented here represent an alternative or supporting method to the existing tools available to address the biomechanics of cancellous bone. [ABSTRACT FROM AUTHOR]

Background: In the context of biomarker discovery and molecular characterization of diseases, laser capture microdissection is a highly effective approach to extract disease-specific regions from complex, heterogeneous tissue samples. For the extraction to be successful, these regions have to satisfy certain constraints in size and shape and thus have to be decomposed into feasible fragments. Results: We model this problem of constrained shape decomposition as the computation of optimal feasible decompositions of simple polygons. We use a skeleton-based approach and present an algorithmic framework that allows the implementation of various feasibility criteria as well as optimization goals. Motivated by our application, we consider different constraints and examine the resulting fragmentations. We evaluate our algorithm on lung tissue samples in comparison to a heuristic decomposition approach. Our method achieved a success rate of over 95% in the microdissection and tissue yield was increased by 10–30%. Conclusion: We present a novel approach for constrained shape decomposition by demonstrating its advantages for the application in the microdissection of tissue samples. In comparison to the previous decomposition approach, the proposed method considerably increases the amount of successfully dissected tissue. [ABSTRACT FROM AUTHOR]

Falls are the second cause of death in the world. This is the reason why systems of falls detection, framed in the telemedicine field, are widely investigated nowadays. However, these systems often result in false positives. In this paper we propose the development of a fall detection system for people. The system is based on the use of a Kinect 2.0 sensor that allows monitoring from one to six patients and an alarm system that sends both a message and an image to the e-mail of the person who is taking care of the patient. The biomechanical analysis of the fall, carried out using iPi Mocap Studio program, and the fall detection algorithm, developed in LabVIEW graphic programming software, allowed measuring the position and velocity values of a selected point in the skeletonization of the person. Different actions were simulated, including walking, sitting, bending and falling. From the position of the point-selected point (spinebase) of the skeleton of the person, the velocity was calculated with the derivative. This characteristic allowed defining the linguistic variables and fuzzy sets to classify the type of movement. The system was validated with 3 people, of different ages and heights, in a controlled environment, achieving an effectiveness of 95.8% and the activation of the alarm system, creating a technological assistant of adequate and reliable aid that guarantees the integrity of the patient. [ABSTRACT FROM AUTHOR]

Continuous 3+2-axis additive manufacturing (AM) is an emerging AM technology that overcomes the signature problems of the need of support structures and the staircase effect of the traditional 3-axis AM. This paper presents a novel process planning framework for automatically generating a multi-axis support-free printing path for continuous 3+2-axis AM of an arbitrary freeform part. The framework is based on the geometric processing of skeletonization and decomposition and is particularly suitable for a part with distinct multiple trunk-branch structures. The physical printing experimental results carried out by the authors indicate that the proposed framework has performed well and fabricated some challenging models with large overhangs and twisty spatial topologies. [ABSTRACT FROM AUTHOR]

Topology optimization using gradient search with negative and positive elliptical masks and honeycomb tessellation is presented. Through a novel skeletonization algorithm for topologies defined using filled and void hexagonal cells/elements, explicit minimum and maximum length scales are imposed on solid states in the solutions. An analytical example is presented suggesting that for a skeletonized topology, optimal solutions may not always exist for any specified volume fraction, minimum and maximum length scales, and that there may exist implicit interdependence between them. A sequence for length scale (SLS) methodology is proposed wherein solutions are sought by specifying only the minimum and maximum length scales with volume fraction getting determined within a specified range systematically. Through four benchmark problems in small deformation topology optimization, it is demonstrated that solutions by-and-large satisfy the length scale constraints though the latter may get violated at certain local sites. The proposed approach seems promising, noting especially that solutions, if rendered perfectly black and white with minimum length scale explicitly imposed and boundaries smoothened, are quite close in performance compared with the parent topologies. Attaining volume-distributed topologies, wherein members are more or less of the same thickness, may also be possible with the proposed approach. [ABSTRACT FROM AUTHOR]

• We present a novel method able to denoise highly noisy 3D shapes while preserving shape edges sharp. • We demonstrate, for the first time, that 3D surface skeletons can be used for feature-preserving shape denoising. • Our method is simple and computationally efficient to implement, making use of existing 3D skeletonization techniques. Skeletons are well-known descriptors that capture the geometry and topology of 2D and 3D shapes. We leverage these properties by using surface skeletons to remove noise from 3D shapes. For this, we extend an existing method that removes noise, but keeps important (salient) corners for 2D shapes. Our method detects and removes large-scale, complex, and dense multiscale noise patterns that contaminate virtually the entire surface of a given 3D shape, while recovering its main (salient) edges and corners. Our method can treat any (voxelized) 3D shapes and surface-noise types, is computationally scalable, and has one easy-to-set parameter. We demonstrate the added-value of our approach by comparing our results with several known 3D shape denoising methods. [ABSTRACT FROM AUTHOR]

Quasi-2D nanoporous gold ultra-thin films have been elaborated and investigated by specific surface approaches. Three different microscopy techniques (Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and Atomic Force Microscopy (AFM)) have been used for the characterizations. A careful statistical analysis of experimental images has been done, thanks to the development of a dedicated image analysis software. It reveals that the inhomogeneous gold nanomesh at low length scale becomes homogeneous at a length scale larger than the biggest pores size of about 2 μ m, with a constant opacity reaching 35%. At such a scale, the ligaments present an average diameter of 20 nm and an average length of 70 nm. While TEM and SEM present similar results, AFM overestimates the geometric characteristics due to tip convolution effect. However, the topology of the nanomesh is not affected. This study also reveals pores with a much larger size in the quasi 2D nanoporous ultra-thin film than in its bulk counterpart for similar ligaments diameters, which could play an important role in its mechanical properties. • Comparison of microscopy imaging on quasi-2D gold nanomesh. • Topology analysis performed via skeletonization algorithm. • Inhomogeneity observed at a nano length scale. • Homogeneity revealed at a micro length scale larger than 2 μ m, the biggest pore size. [ABSTRACT FROM AUTHOR]

A novel and general method for a fast calculation of scattering/radiation fields is proposed by expressing the source-field relationship through the method of moments (MoM). The scattering fields in the observation region are expanded by a set of SWGs defined on an auxiliary mesh. The associated expansion coefficients are obtained from matrix vector multiplication (MVM) of the impedance matrix in the MoM and the equivalent currents. The proposed method can enable an accurate near-field calculation without a special treatment of the singularity. Numerical experiments on targets with complex configurations are conducted to validate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Background: In this study, we proposed an averaged airway model design based on four healthy subjects and numerically evaluated its effectiveness for predicting the airflow and particle transport through an airway. Methods: Direct-averaged models of the conducting airways of four subjects were restored by averaging the three-dimensional (3D) skeletons of four healthy airways, which were calculated using an inverse 3D thinning algorithm. We simulated the airflow and particle transport in the individual and the averaged airway models using computational fluid dynamics. Results: The bifurcation geometry differs even among healthy subjects, but the averaged model retains the typical geometrical characteristics of the airways. The Reynolds number of the averaged model varied within the range found in the individual subject models, and the averaged model had similar inspiratory flow characteristics as the individual subject models. The deposition fractions at almost all individual lobes ranged within the variation observed in the subjects, however, the deposition fraction was higher in only one lobe. The deposition distribution at the main bifurcation point differed among the healthy subjects, but the characteristics of the averaged model fell within the variation observed in the individual subject models. On the contrary, the deposition fraction of the averaged model was higher than that of the average of the individual subject models and deviated from the range observed in the subject models. Conclusion: These results indicate that the direct-averaged model may be useful for predicting the individual airflow and particle transport on a macroscopic scale. [ABSTRACT FROM AUTHOR]

Estimation of time of death is an intrinsic part of the medico-legal investigation. The forensic anthropologist requires an innate knowledge of the human skeleton, which includes various anatomical planes of reference, the features of skeletal tissue at various levels, internal features of the bone to estimate the time since death. According to various researches ages of skeletons are determined by various methods like DNA profiling, anthropometry. Various changes are observed at decomposing phases which include putrefaction, mummification, and many others. After the skeletonization, various challenges have been faced by researchers. Hence postmortem changes were examined using microradiography, electron microscopy and UV fluorescence examination of the cross section of bones, chemical methods like radiocarbon dating provides information to decode the time of death of skeletal remains. This review gives knowledge about the use of gross examination of bone, physical, chemical methods carried out on the bone for determining the time since death. [ABSTRACT FROM AUTHOR]

• A system was developed by using a side-viewing Kinect – v2 for sorghum plants phenotyping. • The skeletonization algorithm can segment stems and individual leaves of sorghum plants with overlapping tillers. • The system-derived traits were found to have high correlations with the corresponding manual measurements. • The total leaf area and stem volume showed promising potential for biomass prediction. The ability to correlate morphological traits of plants with their genotypes plays an important role in plant phenomics research. However, measuring phenotypes manually is time-consuming, labor intensive, and prone to human errors. The 3D surface model of a plant can potentially provide an efficient and accurate way to digitize plant architecture. This study focused on the extraction of morphological traits at multiple developmental timepoints from sorghum plants grown under controlled conditions. A non-destructive 3D scanning system using a commodity depth camera was implemented to capture sequential images of a plant at different heights. To overcome the challenges of overlapping tillers, an algorithm was developed to first search for the stem in the merged point cloud data, and then the associated leaves. A 3D skeletonization algorithm was created by slicing the point cloud along the vertical direction, and then linking the connected Euclidean clusters between adjacent layers. Based on the structural clues of the sorghum plant, heuristic rules were implemented to separate overlapping tillers. Finally, each individual leaf was automatically segmented, and multiple parameters were obtained from the skeleton and the reconstructed point cloud including: plant height, stem diameter, leaf angle, and leaf surface area. The results showed high correlations between the manual measurements and the estimated values generated by the system. Statistical analyses between biomass and extracted traits revealed that stem volume was a promising predictor of shoot fresh weight and shoot dry weight, and the total leaf area was strongly correlated to shoot biomass at early stages. [ABSTRACT FROM AUTHOR]

Integral equations are commonly encountered when solving complex physical problems. Their discretization leads to a dense kernel matrix that is block or hierarchically low-rank. This paper proposes a new way to build a low-rank factorization of those low-rank blocks at a nearly optimal cost of O(nr) for an n×n block submatrix of rank r. This is done by first sampling the kernel function at new interpolation points, then selecting a subset of those using a CUR decomposition and finally using this reduced set of points as pivots for a rank-revealing LU-type factorization. We also explain how this implicitly builds an optimal interpolation basis for the kernel under consideration. We show the asymptotic convergence of the algorithm, explain its stability, and demonstrate on numerical examples that it performs very well in practice, allowing us to obtain rank nearly equal to the optimal rank at a fraction of the cost of the naive algorithm. [ABSTRACT FROM AUTHOR]

Graphical abstract Example of the quntitative analysis of hydroxyapatite crystals. Abstract Bones are complex nanocomposites composed mainly by hydroxyapatite nanocrystals. Different factors characterize its morphology: composition, length, orientation, roughness. To increase our understanding of the tissue morphology at this fundamental lever of organization, a new method based on the straight skelonization of the images obtained by electronic microscopy is proposed. The method detects and measures the length and angularity of any straight edge of over the image. The technique resolved several test patterns independent of size and angle of rotation. Several samples obtained from different substrates were analyzed with the method. The results were consistent with those values obtained from conventional methods. Although still limited as a laboratory application, shape analysis has the potential to provide insight into the mechanisms of crystal growing and may provide a basis for specifications or guidelines for the manufacturing of biomaterial for bone tissue engineering. Our proposed automated computational method for the analysis and quantification digital images of bone tissue at microscale provide a rapid and accurate of the mechanical properties of the tissue. [ABSTRACT FROM AUTHOR]

Many skeletonization methods are available to simplify the configuration of urban water distribution systems (WDS) to enable hydraulic modeling and analysis. However, these approaches are generally based on steady-state hydraulic analysis, and hence the skeletonized systems cannot represent the underlying transient properties of the original systems, resulting in potential risk when handling transient events (e.g., pipe bursts). To this end, this paper proposes a transient-based method to ensure the skeletonized systems can capture the overall transient properties of the original WDS. Two criteria are proposed as principles to skeletonize pipes in series, and three assessment metrics are adopted to evaluate the transient performance of the skeletonized systems. Two WDS are used to demonstrate the effectiveness of the proposed method. Results show that the skeletonized systems produced by the proposed approach match well with the original WDS in transient dynamics. Although not all transient details can be captured, the proposed approach significantly outperforms the traditional steady-state--based method. The proposed approach offers an important tool to enable effective skeletonization of WDS for transient modeling and analysis. [ABSTRACT FROM AUTHOR]

• A deep learning, PoreSkel, is developed for extracting skeleton and distance maps from porous media images. • The model demonstrated high robustness and generality with tested on 20 different sandstone and carbonate samples. • The model works directly on unprocessed grayscale images, eliminating the need for traditional image processing. • PoreSkel outperforms traditional models in handling disruptions caused by minerals and perturbations in pore spaces. • The model provides a more representative pore structure, leading to improved pore network analyses. Skeletonization, a crucial step in pore network modeling, traditionally involves the extraction of skeleton pixels from binarized, segmented X-ray images of porous materials. However, this conventional approach often suffers from user bias during segmentation, potentially leading to the loss of essential image details. This study addresses this limitation by developing deep learning model, called PoreSkel, designed to directly perform skeletonization and distance map extraction from unprocessed grayscale images, thus eliminating the need for additional image processing steps. The model was trained, validated, and tested using an expansive databank of micro-CT images from 20 distinct sandstones, carbonates, and sand pack samples, a total of 10,240 images, with each sample represented by a cube of size 5123. A fifth of these images, specifically 15.6 % from sixteen sandstone and sand pack samples, were used for training, while the remainder served for model validation (4.4 %) and extensive testing (80 %). PoreSkel showed an excellent performance, achieving a mean f1-score of 0.964 for skeletonization and an RMSE of 0.057 for distance map extraction during the testing phase. Our assessments revealed that the model is robust to bias toward the majority class, namely the background pixels. Furthermore, the model showed high generality, maintaining its performance when tested using unseen images from three carbonates and an additional sandstone. Notably, PoreSkel effectively handles disruptions caused often by the presence of minerals in pore spaces and perturbations on pore boundaries - a common challenge for the medial axis technique - resulting in fewer nodes (i.e., pore junctions) and pore coordination numbers, but a higher number of connected skeletons. Therefore, PoreSkel provided a more precise and representative pore structures of porous material that is needed for accurate pore network generation and modeling. [ABSTRACT FROM AUTHOR]

Chinese calligraphy is often used to perform the beauty of characters in Chinese culture and is quite suitable in the study of shape representation. The skeleton of a digital line pattern can be treated as the shape descriptor. However, the skeleton-biased and reconstruction-incomplete phenomena often exist in a skeletonization method, which results in the difficulty of using the skeleton to perform the beauty of Chinese calligraphy characters. To overcome this difficulty, skeletal line information derived from the skeletal points and indexed boundary points is defined, and its transformation is implemented by a procedure of two-phase skeletal line placement (SLP). Based on the SLP, an effective algorithm including the SLP-stroke for strokes, SLP-fork for forks, and SLP-end for the end parts of strokes is developed for constructing the skeletal line-based shape descriptor. Four indices of measurement of skeleton deviation, number of distorted forks, number of spurious strokes, and measurement of reconstructability are used to evaluate the performance of the proposed approach. Experimental results show that the skeleton-biased phenomenon can be greatly reduced and the pattern reconstructability close to 100% is achieved, thus confirming that the proposed skeletonization approach is suitable for the Chinese calligraphy character representation and reconstruction. [ABSTRACT FROM AUTHOR]

Although the post-mortem interval (PMI) is essential in forensic sciences, dating skeletonized remains is a complex task for forensic scientists, not only because of the lack of reliable methods that currently exist for its estimation but also due to the variability of the cadaveric decomposition process, which involves a series of factors. Weathering and breakdown of remains progresses with time, from cracking to loss of shape, and is accepted to occur in observable stages. When dealing with buried remains, these processes will take longer because many of the most destructive agents will be shut out. Burial represents a unique environment which has not been examined often. This study analysed bone weathering (weight loss, grease, degradation, fractures and flaking) of the atlas, axis, humerus, femur and first metatarsal of 86 individuals recovered from a Portuguese cemetery plot. Sex, age-at-death, burial period and storage period were taken into account, but several problems may have affected the outcome of the study. However, PMI estimation based on weathering is not reliable, confirming that burial contexts create distinct micro-taphonomic environments. [ABSTRACT FROM AUTHOR]

OBJECTIVES There is growing interest in the use of bilateral internal thoracic arteries (BITAs) for myocardial revascularization. This study sought to compare the balance between early benefits and long-term outcomes of skeletonized or non-skeletonized conduits and to determine whether differences in outcomes are affected by other patient risk factors. METHODS BITAs were used in 1504 cases with either SK or NSK conduits. Propensity matching was completed using 22 covariates identifying 441 pairs of patients. The primary outcomes are the sternal wound infection in the short term and the composite outcome of all-cause mortality, myocardial infarction, revascularization and congestive heart failure. Outcomes were assessed using paired analysis techniques and Cox proportional hazards regression models stratified using the matched pairs. RESULTS Incidences of in-hospital mortality and perioperative myocardial infarction were similar in both groups. There were fewer sternal wound infections in the SK group (5.4 vs 9.1%, P  = 0.033). Homogeneity testing of the relative risk estimates confirmed that there was a protective effect of skeletonization in men that was not demonstrated in women (P  = 0.020). SK had a protective effect in diabetics not seen in non-diabetics (P  = 0.048). The composite outcome of all-cause mortality, myocardial infarction, revascularization and congestive heart failure at a median of 5.6 years was comparable in both groups (hazard ratio 0.81, 95% confidence interval 0.57–1.15). CONCLUSION Skeletonization results in better perioperative outcomes and comparable cardiac outcomes in patients undergoing BITA with the greatest benefit in men and patients with chronic obstructive pulmonary disease. [ABSTRACT FROM AUTHOR]

The problem presented in this edition of the Battle of the Water Networks is to define district metering areas (DMAs) in a large network. The problem is addressed in two phases. First, the complexity of the network is simplified by dividing it into three operational areas. Second, an optimization algorithm defines DMAs, looking for the best feasible solution. A preliminary simulation of the network is made. From this, engineering judgment allows for defining an initial set of elements suitable to change. In the second stage, a heuristic algorithm is used to search for the best DMA definition by selecting the locations and settings of the pressure-reducing valves and isolation valves. The network is then divided into two categories: the main pipes and the distribution pipes. Only the distribution pipes can be closed. With these restrictions and those described in the problem, the algorithm looks for the best DMA definition based on both the pressure and demand distribution among all the DMAs. [ABSTRACT FROM AUTHOR]

Skeletonization is employed to accelerate the multilevel fast multipole algorithm (MLFMA) solution of the method of moments matrix system arising from volume integral equations (VIEs). The acceleration is conducted in two aspects: 1) speedup of the calculation of near-field interactions of the MLFMA and 2) improvement of the iterative convergence. Numerical experiments indicate that the proposed algorithm can significantly reduce the runtime and memory usage without degrading the accuracy, in comparison with the VIE solver purely accelerated by the MLFMA. Additionally, for piecewise homogeneous complex plasmonic structures, the proposed algorithm can be more efficient and accurate than the commonly used surface integral equation solver. [ABSTRACT FROM PUBLISHER]

Estimation of the post-mortem interval (PMI) is critical in reconstructing events surrounding death. Despite representing a pertinent legal question, PMI estimation is difficult. This is confirmed by the lack of reliable methods, notably when dealing with skeletonized remains. Some authors present time-successive stages of increasing decay suggesting that the degree of weathering is related to PMI. However, when dealing with buried remains, degradation will take longer because many of the destructive agents will be shut out. This study focused on degradation of remains in a burial context. The remains were scored according to Behrensmeyer and Galloway et al. To understand their reliability when assessing short PMI’s, the remains of two piglets buried for nine months were studied. To test their reliability for assessing longer time-span PMI's (12–19 years), 86 human skeletons buried in coffins were analysed. Over short time-spans, the rate of decay of buried remains followed the referred stages, but the same was not observed over longer time-spans. This paper shows that burial creates distinct micro-taphonomic environments that influence the progression of decay, so these stages should not be used to study buried remains. In conclusion, PMI estimation based on simple variables can be misleading. [ABSTRACT FROM AUTHOR]

In this paper, we bring forth a novel approach of video text detection using Fourier–Laplacian filtering in the frequency domain that includes a verification technique using Hidden Markov Model (HMM). The proposed approach deals with the text region appearing not only in horizontal or vertical directions, but also in any other oblique or curved orientation in the image. Until now only a few methods have been proposed that look into curved text detection in video frames, wherein lies our novelty. In our approach, we first apply Fourier–Laplacian transform on the image followed by an ideal Laplacian–Gaussian filtering. Thereafter K-means clustering is employed to obtain the asserted text areas depending on a maximum difference map. Next, the obtained connected components (CC) are skeletonized to distinguish various text strings. Complex components are disintegrated into simpler ones according to a junction removal algorithm followed by a concatenation performed on possible combination of the disjoint skeletons to obtain the corresponding text area. Finally these text hypotheses are verified using HMM-based text/non-text classification system. False positives are thus eliminated giving us a robust text detection performance. We have tested our framework in multi-oriented text lines in four scripts, namely, English, Chinese, Devanagari and Bengali, in video frames and scene texts. The results obtained show that proposed approach surpasses existing methods on text detection. [ABSTRACT FROM AUTHOR]

Background: Stomatal behavior in grapevines has been identified as a good indicator of the water stress level and overall health of the plant. Microscope images are often used to analyze stomatal behavior in plants. However, most of the current approaches involve manual measurement of stomatal features. The main aim of this research is to develop a fully automated stomata detection and pore measurement method for grapevines, taking microscope images as the input. The proposed approach, which employs machine learning and image processing techniques, can outperform available manual and semi-automatic methods used to identify and estimate stomatal morphological features. Results: First, a cascade object detection learning algorithm is developed to correctly identify multiple stomata in a large microscopic image. Once the regions of interest which contain stomata are identified and extracted, a combination of image processing techniques are applied to estimate the pore dimensions of the stomata. The stomata detection approach was compared with an existing fully automated template matching technique and a semi-automatic maximum stable extremal regions approach, with the proposed method clearly surpassing the performance of the existing techniques with a precision of 91.68% and an F1-score of 0.85. Next, the morphological features of the detected stomata were measured. Contrary to existing approaches, the proposed image segmentation and skeletonization method allows us to estimate the pore dimensions even in cases where the stomatal pore boundary is only partially visible in the microscope image. A test conducted using 1267 images of stomata showed that the segmentation and skeletonization approach was able to correctly identify the stoma opening 86.27% of the time. Further comparisons made with manually traced stoma openings indicated that the proposed method is able to estimate stomata morphological features with accuracies of 89.03% for area, 94.06% for major axis length, 93.31% for minor axis length and 99.43% for eccentricity. Conclusions: The proposed fully automated solution for stomata detection and measurement is able to produce results far superior to existing automatic and semi-automatic methods. This method not only produces a low number of false positives in the stomata detection stage, it can also accurately estimate the pore dimensions of partially incomplete stomata images. In addition, it can process thousands of stomata in minutes, eliminating the need for researchers to manually measure stomata, thereby accelerating the process of analysing plant health. [ABSTRACT FROM AUTHOR]

The traditional grid method for extracting road network has a low accuracy,especially for the extraction of open-pit road network,the loss and offset of road is more significant.For solving this problem,the conventional solution is to enlarge the grid so that the connectivity can be ensured.However,in this paper,by assuming the GPS bias as a normal distribution,a method of rastering the GPS data by calculating the probability of track points on the road was proposed.On this basis,the median filter algorithm was deployed to preprocess the raster image.The index table thinning algorithm was improved,and this improved thinning algorithm was used to refine the grid image of the road network.Finally,the road network was translated into vectorization.Experimental results show that the coverage ratio of this method has been improved by 6.43% to 11.54% compared with the traditional grid method,and the error rate has been reduced by 42.13% to 83.02%.This paper provides an effective method for road network extraction and reveals the important influence of grid size on road network extraction results. [ABSTRACT FROM AUTHOR]

Helical objects occur in medicine, biology, cosmetics, nanotechnology, and engineering. Extracting a 3D parametric curve from a 2D image of a helical object has many practical applications, in particular being able to extract metrics such as tortuosity, frequency, and pitch. We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. The results show that the extracted 3D curve comes within close Hausdorff distance to the ground truth, and has near identical tortuosity for helical objects with a circular profile. Parameter insensitivity and robustness against high levels of image noise are demonstrated thoroughly and quantitatively. [ABSTRACT FROM AUTHOR]

Thinning is an iterative object reduction to obtain skeletons from binary digital pictures. The object boundary is traversed in an iteration step of a sequential thinning algorithm, and the actually visited single point is considered for possible removal. On the contrary, parallel thinning algorithms can remove a set of object points simultaneously. In fully parallel thinning algorithms, the same parallel reduction is applied in each iteration step, and it is repeated until stability is reached. Two thinning algorithms are said to be equivalent if they produce the same result for any input picture. This paper presents the first pair of equivalent sequential and fully parallel 3D surface-thinning algorithms. The proposed algorithms use the same deletion rule, and preserve topology for ( 26 , 6 ) pictures. [ABSTRACT FROM AUTHOR]

A novel technique for identifying and characterising clusters of particles from measurements within a densely seeded two-phase flow is reported. This technique involves the smoothing of normalised instantaneous planar images of particle concentration followed by the application of a robust and unambiguous dynamic threshold to identify particle clusters. Also reported is a method to extract quantitative cluster data including cluster length, width and number of branches. The method employs an algorithm to morphologically skeletonize images of clusters, and subsequently, prune skeleton branches to select those which most strongly represent the shape of the cluster. Together, these techniques have been shown to identify and characterise two-dimensional slices of three-dimensional particle clusters of complex shapes, including those that are bent, wrinkled and branched, with an uncertainty of ≈4% relative to the manually determined values. This method was applied to planar measurements of particles in a heavily seeded turbulent jet with an exit Stokes number of S k D = 1.4 and Reynolds number of R e D = 10 , 000 , based on the pipe diameter, D . The results show that particle clusters are already present at the exit plane and have a characteristic width that is narrowly distributed around an average value of ≈0.17 D . This implies that particle clusters are generated inside the pipe at this preferred length scale. The results also show that the average cluster length at the pipe exit is ≈1.0 D , which, together with the observation that the clusters are oriented at oblique angles to the axis of the jet, suggests that the length of these clusters within the pipe is limited by the pipe diameter. The aspect ratio of the cluster slices was found to be typically A R ≈ 6 − 7 , consistent with the observations that the clusters form long, thin, filament-like structures. [ABSTRACT FROM AUTHOR]

According to the study of muscular type artery, radial artery has all inherent in this type of vessel shell. In their different ways of allocating the radial artery revealed that the structural safety of the shells of the radial artery, especially the inner lining depends on the method of their selection."Skeletonization" leads to disruption of the integrity of the inner shell, especially its endothelial layer, which is the most vulnerable. Deendotelizatsiya inner shell can promote thrombus formation in the graft. [ABSTRACT FROM AUTHOR]

Contours and skeletons are well-known shape representations that embody visual information by using a limited set of object points. Both representations have been applied in various pattern recognition applications, while studies in cognitive science have investigated their roles in human perception. Despite their importance has been shown in the above-mentioned fields, to our knowledge no existing studies have been conducted to compare their performances. Filling this gap, this paper is an empirical study of these two shape representations by comparing their performances over different binary image categories and variations. The image categories include thick, elongated, and nearly thin images. Image variations include addition of noise to the contours, blurring, and size reduction. The comparative evaluation is achieved by resorting to object classification (OC) and content-based image retrieval (CBIR) algorithms and evaluation metrics. The main findings highlight the superiority of contours but the improvements observed when skeletons are used for images with noisy contours. [ABSTRACT FROM AUTHOR]

Skeletonization provides an effective and compact representation of objects, which is useful for object description, retrieval, manipulation, matching, registration, tracking, recognition, and compression. It also facilitates efficient assessment of local object properties, e.g., scale, orientation, topology, etc. Several computational approaches are available in literature toward extracting the skeleton of an object, some of which are widely different in terms of their principles. In this paper, we present a comprehensive and concise survey of different skeletonization algorithms and discuss their principles, challenges, and benefits. Topology preservation, parallelization, and multi-scale skeletonization approaches are discussed. Finally, various applications of skeletonization are reviewed and the fundamental challenges of assessing the performance of different skeletonization algorithms are discussed. [ABSTRACT FROM AUTHOR]

The radial artery is increasingly used as a second arterial conduit for myocardial revascularization. However, the radial artery is susceptible to vasospasm, which is thought to be the principal cause of graft failure. The radial artery is harvested as a skeletonized or a non-skeletonized graft, but the effect of different harvesting technique remains unknown. In this study, we compared the early- and mid-term angiographic findings to elucidate its influence on the graft luminal diameter. We harvested 39 radial arteries either as a skeletonized ( n = 18) or a non-skeletonized graft ( n = 21) using an ultrasonic scalpel. We constructed a composite straight graft by combining a right internal thoracic artery and a radial artery. All the radial artery grafts were sequentially anastomosed to coronary arteries. We measured the diameters of the radial arteries before the operation, within 1 month and 1 year after the operation. At early postoperative period, graft diameter was significantly larger in skeletonized grafts. Graft diameter at the point before the first and the second anastomosis was similar in skeletonized grafts, although that was significantly smaller before the second anastomosis in non-skeletonized grafts. However, 1 year after the operation, the graft diameter was comparable and equally reduced after the first anastomosis in both groups. Skeletonization with an ultrasonic scalpel increases the luminal diameter of the radial artery graft at early postoperative period, which, however, reduces possibly as adaptation to graft flow 1 year after the operation. [ABSTRACT FROM AUTHOR]

Reducing branching effect and increasing boundary noise immunity are of great importance for thinning patterns. An approach based on medial axis transform (MAT) to obtain a connected 1-pixel wide skeleton with few redundant branches is presented in this paper. Though the obtained skeleton by MAT is isotropic with few redundant branches, however, the skeleton points are usually disconnected. In order to rend the merits of the MAT and avoid its disadvantages, the proposed approach is composed of distance-map generation, grouping, ridge-path linking, and refining to obtain the connected 1-pixel wide thin line. The ridge-path linking strategy can guarantee the skeletons connected, whereas the refining process can be readily performed by a conventional thinning process to obtain the 1-pixel wide thinned pattern. The performances investigated by branching effect, signal-to-noise ratio (SNR), and measurement of skeleton deviation (MSD) confirm the feasibility of the proposed MAT-based thinning for line patterns. [ABSTRACT FROM AUTHOR]