Compared basic stitch’s consumptions using image analysis, geometrical modelling and statistical techniques

Techniques of medical image processing and analysis play a crucial role in many clinical scenarios, including in diagnosis and treatment planning. However, immense quantities of data and high complexity of the algorithms often used are computationally demanding. As a result, there now exists a wide range of techniques of medical image processing and analysis that require the application of high-performance computing solutions in order to reduce the required runtime. The main purpose of this review is to provide a comprehensive reference source of techniques of medical image processing and analysis that have been accelerated by high-performance computing solutions. With this in mind, the articles available in the Scopus and Web of Science electronic repositories were searched. Subsequently, the most relevant articles found were individually analyzed in order to identify: (a) the metrics used to evaluate computing performance, (b) the high-performance computing solution used, (c) the parallel design adopted, and (d) the task of medical image processing and analysis involved. Hence, the techniques of medical image processing and analysis found were identified, reviewed, and discussed, particularly in terms of computational performance. Consequently, the techniques reviewed herein present the progress made so far in reducing the computational runtime involved, and the difficulties and challenges that remain to be overcome.

In general, image analysis techniques have been used to analyse images from single 2D sensors, for example 2D images created from an infrared camera. This paper introduces sensory images that are constructed from several 1D sensors, for example a sensory image created from several force sensors on a robot arm. These images are abstract and may not have any visual meaning. In this paper, some transformations from sensor data to sensory images are explained and some of the image processing and analysis techniques that can be applied to such images are discussed. Experimental results are also presented. >

Sizing of programmed defects on optical proximity correction (OPC) feature sis addressed using high resolution scanning electron microscope (SEM) images and image analysis techniques. A comparison and analysis of different sizing methods is made. This paper addresses the issues of OPC defect definition and discusses the experimental measurement results obtained by SEM in combination with image analysis techniques.

Three-dimensional modeling of Virtual reality can be divided into four phases: geometric modeling, physical modeling, motion modeling and behavior modeling, This paper describes the geometric modeling stage, modeling techniques and model optimization technology used to create the Southern Gardens.

Many changes occur in the structure and properties of a test material during drying as a consequence of moisture evaporation. The use of image acquisition and analysis techniques is proposed here as a potential method of obtaining a better understanding of the different phenomena that can happen during drying. Such techniques can quantify the morphological, textural, and color features of materials and the changes that occur in them. The techniques are convenient to use, accurate, and facilitate rapid measurement. Accordingly, the use of image acquisition and analysis techniques continues to attract considerable research interest in the field of drying. Many such techniques have been applied in this field: scanning electron microscopy (SEM), charge-coupled device (CCD) photography, neutron radiography (NR), magnetic resonance imaging (MRI), X-ray tomography, and so forth. Each technique has its own characteristics and specific applications. SEM is employed to investigate the morphological structure and pore distribution of a sample during drying in the form of magnified 2D images. A computer vision system typically uses two portable CCD cameras to provide 2D top- and side-view images of the sample. These can be used for online monitoring of the change in shape and color and any crack development in the sample during drying. NR and MRI are used for determination of the moisture profiles inside the sample during drying. In addition, MRI can be used to characterize the pore distribution in combination with other technologies. X-ray tomography provides 2D cross sections and 3D tomographic reconstructions of the sample, which can be used to elucidate the volume, crack development, surface area, porosity, and moisture profiles of the sample during drying. Overall, of all these various image acquisition and analysis techniques, X-ray tomography is considered to be the one that has the most promising future in the field of drying.

Studies into the evolution and development of leaf shape have connected variation in plant form, function, and fitness. For species with consistent leaf margin features, patterns in leaf architecture are related to both biotic and abiotic factors. However, for species with inconsistent leaf shapes, quantifying variation in leaf shape and the effects of environmental factors on leaf shape has proven challenging. To investigate leaf shape variation in a species with inconsistently shaped leaves, we used geometric morphometric modeling and deterministic techniques to analyze approximately 500 digitized specimens of Capsella bursa-pastoris collected throughout the continental United States over 100 years. We generated a morphospace of the leaf shapes and modeled leaf shape as a function of environment and time. Leaf shape variation of C. bursa-pastoris was strongly associated with temperature over its growing season, with lobing decreasing as temperature increased. While we expected to see changes in variation over time, our results show that the level of leaf shape variation was consistent over the 100 years. Our findings showed that species with inconsistent leaf shape variation can be quantified using geometric morphometric modeling techniques and that temperature is the main environmental factor influencing leaf shape variation.

Musculoskeletal disorders such as osteoarthritis, bone fractures, osteoporosis, or ligament injuries are highly prevalent conditions affecting muscles, bones, joints, and adjacent connective tissues. In 2020, they affected over 1.63 billion people worldwide (GBD 2021 Other Musculoskeletal Disorders Collaborators, 2023). Musculoskeletal disorders cause various symptoms such as pain and mobility limitations, and they have a tremendous impact on the quality of life of an individual imposing a large economic burden to a society (Liu et al., 2022;Parto et al., 2023). The underlying pathophysiological processes and clinical manifestations vary depending on the affected tissue and specific disorder.Imaging provides visualization of the anatomy and physiological processes of the body and plays an important role in the diagnostics of musculoskeletal disorders both in clinical practice and research. Conventional radiography and computed tomography (CT) are usually used to assess changes in the mineralized tissues, such as subchondral bones, whereas magnetic resonance imaging (MRI) is best suited for assessing changes in the soft tissues, for example damage in tendons, ligaments, menisci, and cartilage. Novel imaging, image processing, and image analysis techniques have a great potential to enable earlier diagnosis and deeper understanding of musculoskeletal disorders and pathophysiological processes related to them (Kijowski and Fritz 2023) The aim of this Research Topic was to collect articles showcasing applications of novel and innovative imaging, image processing, and image analysis techniques for assessing musculoskeletal disorders and the underlying pathophysiological processes. Although musculoskeletal conditions can affect various joints, and no specific restrictions were placed on this research topic, the articles included in this research topic focused on disorders involving the spine, spinal joints, and associated muscles.

The process simulation of virtual machining is the key technique in the CNC simulation system. So the paper talks about some useful geometric modeling techniques in simulation field, and bring forward an improved object-space separating modeling technique based on the idea of Dexel and the data-type of Z-MAP, which is a kind of geometric modeling for pieces for milling process simulation. This method is to a certain degree reduced calculation quantities in simulation, increased the speed of simulation and optimized the effect of simulation.

In this study the feasibility of using the latest image capture, processing, and analysis techniques in the oyster embryo-larval development (OEL) test was assessed. This initially involved determining whether the OEL test could be carried out in multiwell plates (which would assist in the application of the image analysis technique), based on data from tests with the reference toxicant zinc and industrial effluents. The study then ascertained which of the 31 image analysis parameters of the Image Pro Plus software used was most appropriate for differentiating between the D larvae and non-D larvae at the end of the test procedure in a manner similar to that of visual observations. On the basis of the zinc reference toxicant and effluent test data derived in this study, the OEL test can be effectively carried out in 24 chamber multiwell plates, which provides the opportunity to count objects with image analysis software. The use of the image analysis parameters area and size (length) in combination resulted in mean control abnormalities and EC50 values in zinc reference toxicant tests which were not significantly different statistically from corresponding values derived using visual observations. Discrimination using the area and length parameters may be improved by the inclusion of other parameters in a suite of measurements which would reduce interference from extraneous material or lighting artefacts. Furthermore, the use of multiwell plates and image analysis can eliminate the variability associated with sub-sampling and inter-operator differences in the counts of D larvae and non-D larvae which is evident with the current visual observation method.

Three-dimensional tow inclination model for calculating elastic constants of three-dimensional triaxial braided composites

Type-2 Fuzzy Set Theory (T2FST) is widely used for defining uncertainty data points rather than the traditional fuzzy set theory (type-1) since 2001. Recently, T2FST is used in many fields due to its ability to handle complex uncertainty data. In this paper, a review of normal type-2 fuzzy geometric curve modeling methods and techniques is presented. In particular, there have been recent applications of Normal Type-2 Fuzzy Set Theory (NT2FST) in geometric modeling, where it has helped improving results over type-1 fuzzy sets. In this paper, a concise and representative review of the processes in normal type-2 fuzzy geometrical curve modeling such as the fuzzification is presented.

Virtual-real fusion is a typical feature of digital twin technology, and the geometric scenes of digital twins are mainly achieved through geometric modelling techniques. To solve the problem of insufficient accuracy and low automation level in scene geometric modelling. A high-precision simulation scene generation framework based on calibration balls is proposed to guide geometric modelling. We propose a point cloud segmentation model, Small Scale Segmentation Network (SSSNet), to improve segmentation accuracy, especially for calibration ball recognition in cluttered scenes. More specifically, a hybrid attention module is proposed for fusing multi-source features to guide the network in learning the correlation between features. In addition, a novel balloon simulation algorithm was proposed to achieve adaptive extraction of regions of interest. Finally, geometric feature descriptors are introduced to enrich features and reduce interference from neighbouring point clouds. The results indicate that the segmentation accuracy has been significantly improved compared to existing methods. Meanwhile, the proposed framework has more advantages in simulating scene generation problems.

Computational models of the mitral valve (MV) exhibit significant potential for patient-specific surgical planning. Recently, these models have been advanced by incorporating MV tissue structure, non-linear material properties, and more realistic chordae tendineae architecture. Despite advances, only limited ground-truth data exists to validate their ability to accurately simulate MV closure and function. The validation of the underlying models will enhance modeling accuracy and confidence in the simulated results. A necessity towards this aim is to develop an integrated pipeline based on a comprehensive in-vitro flow loop setup including echocardiography techniques (Echo) and micro-computed tomography. Building on [1] we improved the acquisition protocol of the proposed experimental setup for in-vitro Echo imaging, which enables the extraction of more reproducible and accurate geometrical models, using state-of-the art image processing and geometric modeling techniques. Based on the geometrical parameters from the Echo MV models captured during diastole, a bio-mechanical model is derived to estimate MV closure geometry. We illustrate the framework on two data sets and show the improvements obtained from the novel Echo acquisition protocol and improved bio-mechanical model.

Particle simulations as well as geometric modeling techniques have demonstrated their ability to process and render points interactively. However, real-time particle-based fluid simulations suffer from poor rendering quality due to low surface particle resolutions. Surfaces appear blobby, surface details are lost, and features like edges are degraded due to smoothing effects. This paper presents a novel point refinement method for irregularly sampled, dynamic points coming from a particle-based fluid simulation. Our interpolation algorithm can handle complex geometries including splashes, and at the same time preserves features like edges. Point collisions are avoided resulting in a nearly uniform sampling facilitating surface reconstruction techniques. No point preprocessing is necessary, and point neighborhoods are dynamically updated reducing computation and memory costs. We show that our algorithm can efficiently detect and refine the surface points of a fluid and we demonstrate the improvement of rendering quality and applicability to real-time simulations.

Bi-exponential proton transverse relaxation rate (R 2) image analysis using RF field intensity-weighted spin density projection: potential for R 2 measurement of iron-loaded liver