Hemostasis is a defence mechanism that prevents blood losses in cases of vessel injuries, and other related disorders. In many cases, patients need to frequently monitor their blood coagulation tendency in order to re...
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ISBN:
(纸本)9781665462198
Hemostasis is a defence mechanism that prevents blood losses in cases of vessel injuries, and other related disorders. In many cases, patients need to frequently monitor their blood coagulation tendency in order to regulate their medication. In addition, red blood cell aggregation (RBCA) is related to blood inflammation, and it appears elevated in many pathological conditions. Blood coagulation and RBCA can be studied by analysing the dynamic changes of light transmittance though a clotting/aggregating sample, and indeed various works in the literature exploit this approach. In this work, blood coagulation and RBCA are examined by utilising single drops of blood in an inexpensive camera-based microfluidic system, designed for low computational and production cost. Results are compared with a microscopy-camera system, with both setups utilizing the same custom made microchannel. Three imageprocessingalgorithms are developed to analyze the averaged light intensity, and the local structural chracteristics of blood, through a binarization and region classification method, using logical operations. The results illustrate the repeatability of the technique and the donorto-donor variation within the proposed approach. Based on the imageprocessing analysis, the developed coagulation and aggregation indices show great potential of utilisation in an inexpensive and robust point of care device.
PIFuHD can generate high-resolution model in the process of human 3D reconstruction. However, PIFuHD will produce debris outside the human body when the image background is more complex. In order to solve this problem...
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ISBN:
(纸本)9783031192135;9783031192142
PIFuHD can generate high-resolution model in the process of human 3D reconstruction. However, PIFuHD will produce debris outside the human body when the image background is more complex. In order to solve this problem, this paper develops an adaptive BSCO algorithm for the background of human body and image of human body in 3D reconstruction system. The BSCO algorithm is divided into four steps in processing. First, BSCO algorithm uses Go-selfies to separate the background. Second, BSCO algorithm converges the RGB of all pixels of the character into a set. Third, BSCO algorithm finds the greatest difference from the set through HSV conversion. Fourth, BSCO algorithm weighs the set and then calculates the RGB score. The highest score of RGB is used as the RGB of the background after solid color optimization. The experimental results show that the proposed method improves the reconstruction effect of PIFuHD.
Photon-counting CT (PCCT) is an emerging x-ray spectral imaging technology. There are several PCCT prototypes available for clinical and experimental applications. Despite many published results, objective quantitativ...
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ISBN:
(纸本)9781510671553;9781510671546
Photon-counting CT (PCCT) is an emerging x-ray spectral imaging technology. There are several PCCT prototypes available for clinical and experimental applications. Despite many published results, objective quantitative evaluation of PCCT systems remains challenging due to varied and unknown influences. In addition, CT acquisition geometry and imageprocessing mechanisms are often proprietary, complicating the correlations between the detector's physical characteristics and the corresponding CT image quality, hindering fair comparisons between different technologies. This study aimed to provide a resource to address these challenges by developing a versatile model that accurately replicates the physics of any semiconductor-based photon-counting detector (PCD) and integrating it into a virtual imaging framework to generate detector-specific CT images. The methodology involved a Monte Carlo simulation to model x-ray photon interactions with PCDs and an analytical Gaussian charge sharing model to model charge-diffusion and -repulsion in the detector. Finally, the energy deposited post-crosstalk by source photons (1-120 keV) in the 3x3-pixel-neighborhood was translated into photon counts across two energy thresholds to compute detector-specific spatio-energetic covariance correlation matrices. This framework was validated against experimental measurements of a clinical CdTe-based PCCT, showcasing its accuracy in reproducing real-world scenarios. Additionally, to demonstrate the model's efficacy, we simulated key PCD materials (Si, CdTe, CZT) and designed standardized scanner components, developing virtual systems (DukeCounter scanners). These systems were used to "scan" a physics phantom (ACR) and anthropomorphic-computational models (XCAT). In low-energy (i.e., 5 keV for Si, 20 keV for CdTe and CZT) threshold images, for 125 mAs acquisitions, (noise magnitudes, HU for bone insert) measured in ACR phantom were (76.0 HU, 889.4 HU), (76.9 HU, 932.9 HU), (81.7 HU, 939.4 HU)
Visible-infrared composite cameras are widely used in public health monitoring and intelligent security. Fast and accurate registration of visible-infrared images is the key to the further application of the informati...
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The widespread utilization of three-dimensional reconstruction technology across various domains such as medicine, architecture, and transportation has led to a growing demand for precise positioning and high-precisio...
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ISBN:
(数字)9798350386660
ISBN:
(纸本)9798350386677
The widespread utilization of three-dimensional reconstruction technology across various domains such as medicine, architecture, and transportation has led to a growing demand for precise positioning and high-precision modeling of targets. Three-dimensional reconstruction methodologies leveraging deep learning techniques have demonstrated significant advantages. Nonetheless, traditional three-dimensional reconstruction networks often encounter challenges related to loss of intricate image features, low point cloud density, and susceptibility to generating voids, consequently impacting quality and accuracy of three-dimensional reconstructions. To combat this challenge, this study introduces an algorithm based on graph neural networks for dynamically selecting central points as a replacement for the original point cloud enhancement strategy. Initially, the algorithm employs CAS method to identify appropriate central points that cover expanded spatial volumes within their respective neighborhoods. Subsequently, PointFlow algorithm is applied to forecast point clouds at these central points. The resulting point clouds are then refined by integrating original point cloud segments with interpolated point cloud segments, culminating in comprehensive, high-density three-dimensional point clouds representing the target scene. Relative to Point-MVSNet, the algorithm presented in this paper demonstrates a substantial 6.5% reduction in the average error of the reconstructed three-dimensional models. Notably, the resulting point cloud density and fidelity are elevated, showcasing richer detailed features while also exhibiting lower resource consumption compared to alternative three-dimensional reconstruction algorithms.
Deep neural networks are known to be vulnerable to adversarial attacks (AA).For an image recognition task, this means that a small perturbation of the original can result in the image being *** of such attacks as well...
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Due to the progress of computer technology, imageprocessing-based applications become more and more important not only in advanced research fields but also in our daily life. For example, biomedical imageprocessing,...
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The complex time-variant Doppler frequency of maneuvering targets leads to serious defocusing of inverse synthetic aperture radar (ISAR) imaging results. It indicates the maneuvering motion poses great challenges to t...
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Melanoma is a deadly kind of skin cancer which can spread to other parts of the body. Therefore, it is necessary to identify melanoma at the beginning level. Visual examinationat the time of medical examination of ski...
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Autonomous vehicles and Advanced Driving Assistance systems (ADAS) have the potential to radically change the way we travel. Many such of such vehicles currently rely on segmentation and object detection algorithms to...
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