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Computers in biology and medicine 30건

  1. [해외논문]   Editorial Board   SCI SCIE SCOPUS


    Computers in biology and medicine v.95 ,pp. ii - ii , 2018 , 0010-4825 ,

    초록

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    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  2. [해외논문]   QR-decomposition based SENSE reconstruction using parallel architecture   SCI SCIE SCOPUS

    Ullah, Irfan (Corresponding Author. Room 402 Cubator 1ne, Medical Image Processing Research Group Lab, Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan.) , Nisar, Habab , Raza, Haseeb , Qasim, Malik , Inam, Omair , Omer, Hammad
    Computers in biology and medicine v.95 ,pp. 1 - 12 , 2018 , 0010-4825 ,

    초록

    Abstract Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k -space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Highlights QR decomposition based SENSE algorithm for MR image reconstruction is proposed. Proposed method is successfully implemented on CPU (C,OpenMP) and GPU (CUDA). GPU implementation successfully exploits the inherent parallelism of QR based SENSE. GPU gives (up to) 12x speedup as compare to multi core CPU implementation. GPU gives (up to) 53x speedup as compare to single core CPU implementation.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

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  3. [해외논문]   Appropriate use of the increment entropy for electrophysiological time series   SCI SCIE SCOPUS

    Liu, Xiaofeng (College of IoT Engineering, Hohai University, Changzhou 213022, China ) , Wang, Xue (College of Computer and Information, Hohai University, Nanjing 210098, China ) , Zhou, Xu (College of IoT Engineering, Hohai University, Changzhou 213022, China ) , Jiang, Aimin (College of IoT Engineering, Hohai University, Changzhou 213022, China)
    Computers in biology and medicine v.95 ,pp. 13 - 23 , 2018 , 0010-4825 ,

    초록

    Abstract The increment entropy (IncrEn) is a new measure for quantifying the complexity of a time series. There are three critical parameters in the IncrEn calculation: N (length of the time series), m (dimensionality), and q (quantifying precision). However, the question of how to choose the most appropriate combination of IncrEn parameters for short datasets has not been extensively explored. The purpose of this research was to provide guidance on choosing suitable IncrEn parameters for short datasets by exploring the effects of varying the parameter values. We used simulated data, epileptic EEG data and cardiac interbeat (RR) data to investigate the effects of the parameters on the calculated IncrEn values. The results reveal that IncrEn is sensitive to changes in m , q and N for short datasets ( N ≤ 500 ). However, IncrEn reaches stability at a data length of N = 1000 with m = 2 and q = 2 , and for short datasets ( N = 100 ), it shows better relative consistency with 2 ≤ m ≤ 6 and 2 ≤ q ≤ 8 We suggest that the value of N should be no less than 100. To enable a clear distinction between different classes based on IncrEn, we recommend that m and q should take values between 2 and 4. With appropriate parameters, IncrEn enables the effective detection of complexity variations in physiological time series, suggesting that IncrEn should be useful for the analysis of physiological time series in clinical applications. Highlights IncrEn is suitable to the change detection for short physiological time series. A guidance on choosing suitable IncrEn parameters for short datasets is proposed. IncrEn exhibits a better relative consistency with m and q between 2 and 4, N ≥ 100.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  4. [해외논문]   Deep transfer learning for characterizing chondrocyte patterns in phase contrast X-Ray computed tomography images of the human patellar cartilage   SCI SCIE SCOPUS

    Abidin, Anas Z. (Department of Biomedical Engineering, University of Rochester Medical Center, Rochester, NY, USA ) , Deng, Botao (Department of Electrical Engineering, University of Rochester Medical Center, Rochester, NY, USA ) , DSouza, Adora M. (Department of Electrical Engineering, University of Rochester Medical Center, Rochester, NY, USA ) , Nagarajan, Mahesh B. (Department of Radiological Sciences, University of California Los Angeles, Los Angeles, USA ) , Coan, Paola (European Synchrotron Radiation Facility, Grenoble, France ) , Wismü (Department of Biomedical Engineering, University of Rochester Medical Center, Rochester, NY, USA) , ller, Axel
    Computers in biology and medicine v.95 ,pp. 24 - 33 , 2018 , 0010-4825 ,

    초록

    Abstract Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated to be effective for visualization of the human cartilage matrix at micrometer resolution, thereby capturing osteoarthritis induced changes to chondrocyte organization. This study aims to systematically assess the efficacy of deep transfer learning methods for classifying between healthy and diseased tissue patterns. We extracted features from two different convolutional neural network architectures, CaffeNet and Inception-v3 for characterizing such patterns. These features were quantitatively evaluated in a classification task measured by the area (AUC) under the Receiver Operating Characteristic (ROC) curve as well as qualitative visualization through a dimension reduction approach t-Distributed Stochastic Neighbor Embedding (t-SNE). The best classification performance, for CaffeNet, was observed when using features from the last convolutional layer and the last fully connected layer (AUCs > 0.91 ). Meanwhile, off-the-shelf features from Inception-v3 produced similar classification performance (AUC > 0.95 ). Visualization of features from these layers further confirmed adequate characterization of chondrocyte patterns for reliably distinguishing between healthy and osteoarthritic tissue classes. Such techniques, can be potentially used for detecting the presence of osteoarthritis related changes in the human patellar cartilage. Highlights Phase Contrast Imaging allows visualization of osteoarthritic changes in the patellar cartilage. Features from pre-trained CNNs can be used characterize healthy and diseased patterns. Features from Inception-v3 perform better than CaffeNet and GLCM at the classification task. Fine-tuning with a small dataset can improve classifier performance. Visualization techniques can help further substantiate the characterization obtained.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  5. [해외논문]   Discrete multi-physics simulations of diffusive and convective mass transfer in boundary layers containing motile cilia in lungs   SCI SCIE SCOPUS

    Ariane, Mostapha (School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom ) , Kassinos, Stavros (Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678, Nicosia, Cyprus ) , Velaga, Sitaram (Pharmaceutical Research Group, Division of Medical Science, Department of Health Science, Luleå) , Alexiadis, Alessio (University of Technology, 971 87, Luleå, Sweden )
    Computers in biology and medicine v.95 ,pp. 34 - 42 , 2018 , 0010-4825 ,

    초록

    Abstract In this paper, the mass transfer coefficient (permeability) of boundary layers containing motile cilia is investigated by means of discrete multi-physics. The idea is to understand the main mechanisms of mass transport occurring in a ciliated-layer; one specific application being inhaled drugs in the respiratory epithelium. The effect of drug diffusivity, cilia beat frequency and cilia flexibility is studied. Our results show the existence of three mass transfer regimes. A low frequency regime, which we called shielding regime, where the presence of the cilia hinders mass transport; an intermediate frequency regime, which we have called diffusive regime, where diffusion is the controlling mechanism; and a high frequency regime, which we have called convective regime, where the degree of bending of the cilia seems to be the most important factor controlling mass transfer in the ciliated-layer. Since the flexibility of the cilia and the frequency of the beat changes with age and health conditions, the knowledge of these three regimes allows prediction of how mass transfer varies with these factors. Highlights The Discrete Multi-Physics is applied to boundary layers containing motile cilia (mass transfer). The effect of drug diffusivity, cilia beat frequency and cilia flexibility is investigated. The results show the existence of three mass transfer regimes: Shielding regime, diffusive regime and convective regime.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

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  6. [해외논문]   Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network   SCI SCIE SCOPUS

    Charron, Odelin (Department of Medical Physics, Paul Strauss Center, Strasbourg, France ) , Lallement, Alex (ICube-UMR 7357, Strasbourg, France ) , Jarnet, Delphine (Department of Medical Physics, Paul Strauss Center, Strasbourg, France ) , Noblet, Vincent (ICube-UMR 7357, Strasbourg, France ) , Clavier, Jean-Baptiste (Department of Medical Physics, Paul Strauss Center, Strasbourg, France ) , Meyer, Philippe (Department of Medical Physics, Paul Strauss Center, Strasbourg, France)
    Computers in biology and medicine v.95 ,pp. 43 - 54 , 2018 , 0010-4825 ,

    초록

    Abstract Stereotactic treatments are today the reference techniques for the irradiation of brain metastases in radiotherapy. The dose per fraction is very high, and delivered in small volumes (diameter Highlights a convolutional neural network to detect and segment brain metastases on magnetic resonance images (MRI) is presented. The impact of using multimodal MRI on network performance is studied. Virtual patients and segmentation maps which distinguish the active from the necrotic part of the metastases are evaluated. A comparison between the results we obtained and those of the literature is presented.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  7. [해외논문]   Optimized multi-level elongated quinary patterns for the assessment of thyroid nodules in ultrasound images   SCI SCIE SCOPUS

    Raghavendra, U. (Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India ) , Gudigar, Anjan (Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India ) , Maithri, M. (Department of Mechatronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India ) , Gertych, Arkadiusz (Department of Surgery, Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA ) , Meiburger, Kristen M. (Department of Electronics and Telecommunications, Politecnico di Torino, Italy ) , Yeong, Chai Hong (Department of Biomedical Imaging, University of Malaya, Kuala Lumpur, Malaysia ) , Madla, Chakri (Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand ) , Kongmebhol, Pailin (Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand ) , Molinari, Filippo (Department of Electronics and Telecommunications, Politecnico di Torino, Italy ;) , Ng, Kwan Hoong , Acharya, U. Rajendra
    Computers in biology and medicine v.95 ,pp. 55 - 62 , 2018 , 0010-4825 ,

    초록

    Abstract Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a computer-aided diagnosis (CAD) system can be helpful to cross-verify the severity of nodules. This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. Our CAD algorithm achieved a maximum accuracy of 97.71% and 97.01% in private and public datasets respectively. The evaluation of this CAD system on both private and public datasets confirmed its effectiveness as a secondary tool in assisting radiological findings. Highlights An expert system for the assessment of thyroid nodule is presented. Both public and private datasets are used for the evaluation. Multi-level elongated quinary patterns are used. Particle swarm optimization (PSO) is used for feature selection. Attained maximum accuracy of 97.71% using SVM classifier. Graphical abstract [DISPLAY OMISSION]

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

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  8. [해외논문]   Effect of off-plane bifurcation angles of primary bronchi on expiratory flows in the human trachea   SCI SCIE SCOPUS

    Suh, Youngjoon (Corresponding author. School of Mechanical Engineering, College of Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, 06974, Republic of Korea.) , Park, Joong Yull
    Computers in biology and medicine v.95 ,pp. 63 - 74 , 2018 , 0010-4825 ,

    초록

    Abstract Background The human airway is exposed to the development of diverse flow patterns based on differences in its morphological/geometrical parameters across individuals. Although effects of the asymmetry between the right and left main bronchi on airway flows have been investigated in the past, there exists a paucity in terms of studies that focus on the role of stronger physiological asymmetric features, such as off-plane bifurcation angles of primary bronchi, in expiratory flows. Method Computational fluid dynamic techniques have been used to demonstrate presence of Dean-type secondary flows and vortices in the bifurcation region. Formation of a distinctive pattern was observed corresponding to an increase in the off-plane branching angle. An experiment involving 3D printed airways and smoke was also performed to visualize flow patterns and verify simulation results. Results Good agreement was observed between computational and experimental results. Furthermore, it was revealed that the predicted wall shear stress distribution demonstrated significant changes (with a maximum shear stress increase of 30.7%) compared to conventional airway models that adopt symmetric bifurcation angles. The overall flow demonstrated a swerving motion, which was characterized by tracking the vortex cores (maximum accumulated radial movement of 72.6°) when they ascended towards the trachea inlet in off-plane airway models. Conclusions It was confirmed that off-plane bifurcations in human trachea significantly alter the flow characteristics in expiratory flows. It is expected that the results of this study will provide useful information regarding increasingly advanced patient-specific treatments for respiratory diseases in the trachea. Highlights Asymmetric features of off-plane bifurcating angles of primary bronchi have strong effect on the expiratory flow patterns. Computational simulations were done with LES model and compared with smoke visualization experiments. Dean-type secondary flows and vortices in the bifurcation region exhibit distinctive pattern formation with increases in the off-plane branching angle.

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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    Fig. 1 이미지
  9. [해외논문]   Determining the most significant input parameters in models of subendocardial ischaemia and their effect on ST segment epicardial potential distributions   SCI SCIE SCOPUS

    Johnston, Barbara M. (Corresponding author.) , Johnston, Peter R.
    Computers in biology and medicine v.95 ,pp. 75 - 89 , 2018 , 0010-4825 ,

    초록

    Abstract There is considerable interest in simulating ischaemia in the ventricle and its effect on the electrocardiogram, because a better understanding of the connection between the two may lead to improvements in diagnosis of myocardial ischaemia. In this work we studied subendocardial ischaemia, in a simplified half-ellipsoidal bidomain model of a ventricle, and its effect on ST segment epicardial potential distributions (EPDs). We found that the EPD changed as the ischaemic depth increased, from a single minimum (min1) over the ischaemic region to a maximum (max) there, with min1 over the border of the region. Lastly, a second minimum (min2) developed on the opposite side of the ischaemic region, in addition to min1 and max. We replicated these results in a realistic ventricular model and showed that the min1 only case could be found for ischaemic depths of up to around 35% of the ventricular wall. In addition, we systematically examined the sensitivity of EPD parameters, such as the potentials and positions of min1, max and min2, to various inputs to the half-ellipsoidal model, such as fibre rotation angle, ischaemic depth and conductivities. We found that the EPD parameters were not sensitive to the blood or transverse bidomain conductivities and were most sensitive to either ischaemic depth and/or fibre rotation angle. This allowed us to conclude that the asynchronous development of the two minima might provide a way of distinguishing between low and high thickness subendocardial ischaemia, and that this method may well be valid despite variability in the population. Highlights We studied subendocardial ischaemia in half-ellipsoid and realistic bidomain models. We found three different epicardial patterns: min; max plus min; max plus two mins. The two mins develop asynchronously, this may help identify low and high ischaemia. We used emulators to study the sensitivity of the extrema to nine model inputs. Conductivity values have less effect than fibre rotation and ischaemic depth. Graphical abstract [DISPLAY OMISSION]

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    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

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  10. [해외논문]   Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters   SCI SCIE SCOPUS

    Dill, Vanderson (School of Technology, PUCRS, Porto Alegre, Brazil ) , Klein, Pedro Costa (School of Technology, PUCRS, Porto Alegre, Brazil ) , Franco, Alexandre Rosa (School of Technology, PUCRS, Porto Alegre, Brazil ) , Pinho, Má (School of Technology, PUCRS, Porto Alegre, Brazil) , rcio Sarroglia
    Computers in biology and medicine v.95 ,pp. 90 - 98 , 2018 , 0010-4825 ,

    초록

    Abstract Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy.

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