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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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On the security of a dynamic-hash-table based public auditing protocol

On the security of a dynamic-hash-table based public auditin...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Jianhong Zhang Shuai Liu Jian Mao College of Sciences North China University of Technology Beijing China School of Electronic and Information Engineering Beihang University Beijing China

ISBN: (纸本)9781509037117

Cloud-based data storage is a popular cloud services. It can alleviate data management burden of data owner. However, after data file is transferred to the cloud, data owner is not able to physical dominate these outsourced data file. To efficiently ensure these data intact, several ReD-based integrity checking schemes were presented to ensure data integrity. Due to periodical checking, many data integrity checking schemes makes that the verifier takes high computational cost or communication overhead to verify data intactness. This results in a heavy burden for some schemes. Recently, to ensure secure cloud storage, a dynamic-hash-Table based public auditing protocol was put forward to achieve data privacy protection and data dynamics. An outstanding feature of the protocol is to significantly decease computational cost and communication cost in terms of cloud server and the verifier. Very regretfully, in this work, we will point out that their protocol is not secure. Our attack enables a malicious cloud server to arbitrarily delete or alter the outsourced data without being inspected by the verifier. And We analyze the reason to produce such attack and give a advice to fix the problem. Finally, we also point out that their protocol still exist a security threat: malicious auditor attack, and analyze the corresponding reason to produce such threat.

关键词： Cloud computing Servers Protocols Data models Games Authentication

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Self-adapting Threshold of Pulmonary Parenchyma

Self-adapting Threshold of Pulmonary Parenchyma

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international congress on image and signal processing, biomedical engineering and informatics

作者： Xin-Yue Li Fan Xu Xiao Hu Shao-Hu Peng Hyun-Do Nam Jin-Ming Zhao School of Mechanical and Electric Engineering Guangzhou University China Department of Electronics and Electronical Engineering Dankook University Yongin Korea Department of thoracic surgery The sixth affiliated hospital of Sun Yat Sen University Guangzhou China

ISBN: (纸本)9781509037117

Segmentation for pulmonary parenchyma is a crucial step for computer aided diagnosis (CAD) systems. The accuracy of pulmonary parenchyma segmentation can have a great impact on further steps of CAD systems, such as pulmonary nodule detection and feature extraction. Before segmentation, preprocessing should be done to remove references outside the thorax. After preprocessing, pulmonary parenchyma area threshold will be employed to realize segmentation. However, current segmentation approaches are mainly based on a fixed area threshold, which confronts problem of mis-segmentation and high segmentation failure rate. This article proposed a novel self-adapting threshold segmentation approach, which realized fully automatic segmentation and held considerable accuracy rate. First, fitting of polynomials based on the least square law is constructed to fit curves of pulmonary parenchyma areas. Secondly, a golden standard is created to represent change trend of pulmonary parenchyma for all patients. Finally, the golden standard is adjusted accordingly to realize full adaption and automation of segmentation. Experimental results indicated that the proposed approach achieved excellent accuracy rate and precise segmentation.

关键词： CT image lung segmentation computer aided diagnosis system curve fitting polynomial

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Feature selection algorithm for evoked EEG signal due to RGB colors

Feature selection algorithm for evoked EEG signal due to RGB...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Eman T. Alharbi Saim Rasheed Seyed M. Buhari Information Technology department King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9781509037117

In this paper, a single trial classification is introduced for the Electroencephalography (EEG) signals evoked by RGB colors. The effectiveness of a single trial classification is an important step towards online classification of EEG signals. signals are analyzed by Empirical Mode Decomposition (EMD) technique, and the last decomposition is used in the feature extraction stage. We investigate different feature extraction methods in order to find out the best method which can be used with colors dataset. These methods are: Event-Related Spectral Perturbations (ERSP), Target mean, AutoRegressive and EMD residual. In addition, we propose a new feature selection algorithm, which focuses on selecting the best features by studying the behavior of EEG components that appear due to the introduced color. We introduced a comparison between the classification results of using all extracted features, the results of using the selected features by the proposed algorithm and the results of using the selected features by recursive feature elimination algorithm, which is used by similar study. The proposed algorithm is proved with all the investigated feature extraction methods as the classification accuracies are increased. Support Vector Machine (SVM) is used in the classification process. We found that the execution time of using color's stimulus is only 0.23s, which is much less than the time which was required by any other stimulus such as imagery and spelling word presented in the previous researches. The best feature extraction method that gives the highest classification accuracy and can be used with real time BCI systems are Target Mean and EMD residual, as their accuracies are high and the computation time is very low.

关键词： Electroencephalography image color analysis Feature extraction Support vector machines signal processing algorithms Empirical mode decomposition Color

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A Retrieval System for 3D Multi-Phase Contrast-Enhanced CT images of Focal Liver Lesions Based on Combined Bags of Visual Words and Texture Words

A Retrieval System for 3D Multi-Phase Contrast-Enhanced CT I...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Yingying Xu Lanfen Lin Hongjie Hu Dan Wang Yitao Liu Jian Wang Xianhua Han Yen-Wei Chen College of Computer Science and Technology Zhejiang University Hangzhou China Department of Radiology Sir Run Run Shaw Hospital Hangzhou China Graduate School of Science and Engineering Ritsumeikan University Shiga Japan

ISBN: (纸本)9781509037117

Content-based image retrieval (CBIR) technique for digital image searching has been applied in medical images which are called content-based medical image retrieval (CBMIR). In this paper, we combine texture, density and shape features for CBMIR based on 3D multi-phase contrast enhanced CT images according to radiologists' clinical experience. And a database of 132 focal liver lesions (FLLs) with confirmed pathology type is constructed in this work. We implement bag of visual words (BoVW) model to extract texture features from FLLs based on 3D local binary pattern (LBP) and combine it with conventional intensity-based BoVW. Density and temporal density are designed based on clinical observation. Principle Component Analysis (PCA) is used to extract the sphericity of the lesions as shape features. Experiments performed on the FLLs database show the efficiency of the proposed system and features.

关键词： local binary pattern (LBP) Content-based medical image retrieval (CBMIR) 3D multi-phase contrast enhanced CT images focal liver lesions (FLL) bag of visual texture words (BoTW)

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Pedestrian Detection Based on Deep Learning Model

Pedestrian Detection Based on Deep Learning Model

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international congress on image and signal processing, biomedical engineering and informatics

作者： Hailong Li Zhendong Wu Jianwu Zhang School of Communication Engineering Hangzhou Dianzi University

ISBN: (纸本)9781509037117

Pedestrian detection remains an important task in the theory research and practical application of objects detection. Traditional pedestrian detection algorithms require experts design features to describe the pedestrian characteristics and combine with the classifiers. In recent years, deep learning and especially Convolutional Neural Networks (CNN) have made great success on image and audio, which is the important component of deep learning. Artificial designed methods of feature extracting has an imperfect description of pedestrian in the complex background. In this paper, we propose a pedestrian detection method based on deep convolutional neural network with multi-layers. It can make full use of the advantages of deep convolutional neural network and extract features from the database of pedestrian detection. At the stage of region proposal, to solve the problem of too much redundant windows generated by traditional methods, we use the edge boxes algorithm instead of sliding window algorithm to extract windows. At last, we get a smaller number of windows with high-quality, which is of great importance for the subsequent classification task. At the end of the paper, we carried out multi-sets of comparison experiments in this system. Experiments show that the pedestrian detection system based on deep learning outperforms the traditional methods based on both handcrafted and learned features.

关键词： Feature Extracting Pedestrian Detection Convolution Neural Network (CNN) Deep Learning

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Digit Flexibility and Range of Motion in Carpal Tunnel Syndrome

Digit Flexibility and Range of Motion in Carpal Tunnel Syndr...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Leitong Lin Ke Li Zengcun Su Zhidian Hou Yuanyang Li Xinpei Wang Department of Biomedical Engineering School of Control Science and Engineering Shandong University Jinan China Department of Ultrasound Imaging Shandong Provincial Hospital Affiliated to Shandong University Jinan China Department of Hand and Foot Surgery Shandong Provincial Hospital Affiliated to Shandong University Jinan China Department of Medical Engineering Shandong Provincial Hospital Affiliated to Shandong University Jinan China

ISBN: (纸本)9781509037117

This study investigated effects of carpal tunnel syndrome (CTS) on digit flexibility and range of motion. Twelve healthy, right-handed subjects attended the experiment (6 patients with CTS and 6 healthy controls). The digit flexibility was tested through a Purdue Pegboard Test and the digit's range of motion was tested in process of thumb opposition and thumb circumduction movements. Kinematic signals during thumb movement was recorded using an electromagnetic motion capture system. Additional hand sensorimotor function was assessed using finger sensitivity test, grip strength test and pinch strength tests). The path lengths and interphalangeal (IP) joint angles during thumb opposition and circumduction movements were calculated. Results showed that the path lengths and the angle of the IP joint were significantly lower in the CTS patients compared with controls. At the same time we also found that control group has higher sensitivity than CTS group. There is no obvious change trend for the pinch strength test and grip strength test.

关键词： circumduction movement carpal tunnel syndrome finger flexibility the Purdue Pegboard Test oppoditon movement

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Formation of Graphene Oxide/Graphene Membrane on Solid-State Substrates via Langmuir-Blodgett Self- Assembly

Formation of Graphene Oxide/Graphene Membrane on Solid-State...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Xiao Xie Yuting Shen Litao Sun Key Laboratory of MEMS of Ministry of Education School of Electronic Science and Engineering SEU-FEI Nano-Pico Center Southeast University

ISBN: (纸本)9781509037117

Graphene, an important two-dimensional nanomaterial, is drawing unprecedented, worldwide attention, especially in electronics, energy storage, environmental science and biological engineering. We herein report a convenient protocol for forming a high-quality graphene/graphene oxide (GO) thin membrane on solid-state substrate via the Langmuir-Blodgett self-assembly technique. The process includes layer formation at the liquid-solid-air interface, pulling solid-state substrate vertically from the interface and chemical reduction of the membrane (selective process). Parameters which may alter the properties of membrane have been investigated. The pH was considered the most crucial factor since it affected the smoothness and continuity of the membrane. Pulling cycles had pronounced influence on the thickness of the membrane. Direct formation of the graphene-based membrane on solid-state substrates may eliminate concerns about metal particle residue from the graphene transfer process, incomplete removal of the organic chemicals, and assure the intactness and continuity of the graphene/GO layer. It is therefore believed that the procedure may shed light on the fabrication of high-quality graphene nanodevices.

关键词： Langmuir-Blodgett graphene graphene oxide membrane self-assembly

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Effects of Tactile Sensitivity on Fingertip Center-of-Pressure Distribution During Stable Precision Grip

Effects of Tactile Sensitivity on Fingertip Center-of-Pressu...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Ke Li Na Wei Shouwei Yue Institute of Biomedical Engineering School of Control Science and Engineering Shandong University Department of Geriatrics Qilu Hospital Shandong University Department of Physical Medicine and Rehabilitation Qilu Hospital Shandong University

ISBN: (纸本)9781509037117

This study investigated the effect of tactile sensation on the fingertip center of pressure (COP) signals when the thumb and index finger interact with an object for stable precision grip. Thirty healthy subjects participated in the experiment. The tactile sensitivity was modulated by wrapping up the distal pads of the thumb and index finger with transparent polyethylene films. Subjects were instructed to grip and hold an apparatus as stably as they could for one minute. The apparatus was equipped with an additional load stably fixed or swing at the bottom of the apparatus during precision grip. The COP signals were calculated by the force and torque components, and its distribution was fitted by ellipses using principal component analysis. The area, and the lengths of semi-major and semi-minor axis were computed. Results showed that the tactile deficits did not impair the COP areas. However, with compromised tactile sensation, the semi-major axis of the index finger COP distribution was significantly longer than that of the thumb;and the semi-minor axis of the index finger COP distribution was significantly lower than that of the thumb. These results showed that the tactile deficits may lead to an increase in the inter-digit COP distributions. This study provided a methodology for fingertip COP measurement and has implications of sensorimotor control for precision grip.

关键词： sensorimotor control Precision grip tactile sensation fingertip center of pressures

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Preparation of hollow hafnium oxide microneedles for transdermal drug delivery

Preparation of hollow hafnium oxide microneedles for transde...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Yong-hua Zhang Stephen A. Campbell Department of Electronic Science and Engineering East China Normal University Department of Electrical and Computer Engineering University of Minnesota

ISBN: (纸本)9781509037117

Transdermal drug delivery is an important approach due to its advantages of controlled release, easy wiping off, high safety and low degree of side effects. However, the efficiency and success of the drug delivery method is seriously hampered by the incapacity of many drugs to cross the skin at therapeutically useful rates. A microneedle approach can dramatically promote transdermal delivery, especially for macromolecules. In this paper, a fabrication process for hollow hafnium oxide microneedles on silicon wafer using only one mask has been developed. Photoresist is spun on a 4" silicon (100) wafer and patterned by a mask. Deep reactive ion etching is used to form deep molds inside the wafer. A hafnium oxide film is deposited by atomic layer deposition to cover the top side of the wafer and the inside walls of the molds. Then the back side of silicon wafer is etched by a 30 wt.% KOH solution until exposed hollow hafnium oxide microneedles are obtained. Compared to the processes that have been developed for silicon, silicon oxide, or polymer microneedles, the process presented here is simpler, and the strength and flexibility of hollow hafnium oxide microneedles can be easily adjusted by modifying the depositing time of hafnium oxide films. Hafnium oxide microneedles have potential applications in transdermal drug delivery.

关键词： micro-electromechanical systems micromachining microneedle hafnium oxide atomic layer deposition transdermal drug delivery

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Using electroencephalogram spectral components to assess visual fatigue caused by sustained prism-induced diplopia

Using electroencephalogram spectral components to assess vis...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Yingtuo Wang Tian Liu Shuyin Li Jue Wang National Engineering Research Center of Health Care and Medical Devices Xi'an Jiaotong University Branch Xi'an China

ISBN: (纸本)9781509037117

When the eyes were given maximum disparity, a good relationship was found between visual fatigue and the static or dynamic parameters of vergence and accommodation, as well as physiological signals and subjective evaluation value. The common experimental paradigm of asthenopia is to give the dynamic and repetitive stimulus. Therefore, the current research was proposed to devise a static and sustained stimulus of prism-induced diplopia and projected an experiment to induce visual fatigue by diplopia. Subjects put on the based-out prism whose degree could be adjusted by two pulleys on top of it, they wear their correctional glasses and adjusted slowly the degree of prism until the eyes were diplopia. This state should last for ten minutes in total, of which two minutes as a trial and had an intermediate rested for 30 seconds. The electroencephalogram (EEG) data and critical fusion frequency of 13 subjects were recorded for closed eyes before and after fatigue. In brain occipital, parietal, temporal and frontal lobe, ratio algorithms (α+θ)/β were significantly increased, while gravity frequency (GF) and power spectral entropy (PSE) were significantly reduced, and decline in the critical fusion frequency (CFF) also exists a significant difference. CFF also had a significant difference in the Spearman correlation with PSE, so EEG has a strong correlation with visual fatigue and EEG power spectral components might be a useful method to evaluate the degree of ocular fatigue.

关键词： Visualization Fatigue Electroencephalography Electrodes Physiology Frequency measurement Glass

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