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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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An Automatic Red Blood Cell Counting Method Based on Spectral images

An Automatic Red Blood Cell Counting Method Based on Spectra...

引用

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

作者： Jingyi Lou Mei Zhou Qingli Li Chen Yuan Hongying Liu Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University

ISBN: (纸本)9781509037117

Blood cell analysis, including blood cell counting, is the key point for modern pathological study as well as medical diagnosis. Taking into account both resources and environment of the medical research, analyzing blood cells under the microscope, instead of dedicated blood cell analyzer, provides a more intuitive and convenient way for research uses. This paper aims to provide a method to count red blood cells (RBCs) automatically by analyzing blood cell images collected from a microscopic hyperspectral imaging system. The classification algorithms - spectral angle mappings (SAMs) and support vector machines (SVMs) are used to segment blood cell image. In order to identify RBCs in the image, a standard RBC model has been built to match RBCs in the segmentation results based on SAM classification algorithm. RBC counting results are therefore obtained from the identification and the counting accuracy reaches about 93%. For the sake of higher precision, an improved algorithm, using segmentation results based on SVM classification algorithm to screen the previous matching results, is proposed and the counting accuracy increases to about 98% after applying the improved algorithm.

关键词： RBC counting hyperspectral image blood cell segmentation red blood cells (RBCs)

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Synchrony analysis using different cross-entropy measures of the electroencephalograph activity in Alzheimer's disease

Synchrony analysis using different cross-entropy measures of...

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

作者： Ruofan Wang Dianwei Li Jiang Wang Lihui Cai LianShuan Shi Dept. Information Technology Engineering Tianjin University of Technology and Education Tianjin China Dept. Electrical & Automation Engineering Tianjin University Tianjin China

ISBN: (纸本)9781509037117

In this paper, in order to explore underlying the interaction mechanisms between brain regions, the cross entropy measures: cross sample entropy (C-SampEn) and cross fuzzy entropy (C-FuzzyEn) were used to measure the brain synchrony through analyzing the background electroencephalograph (EEG) signals in Alzheimer's disease (AD) patients. It was demonstrated that the values of both the two features in AD were lower than that of the normal controls, particularly in the alpha band, indicating that the synchrony strength and the information transferring efficiency between the corresponding brain regions were decreased in AD. Moreover, classification results showed that the two cross entropy features could classify AD Group and Control Group correctly. However, the C-FuzzyEn performed better, reflected in the higher classification accuracy. Thus, C-FuzzyEn revealed the abnormalities of brain activity for AD by evaluating the synchrony from EEG series, and it seemed to be an important auxiliary clinical method to diagnose AD early.

关键词： Entropy Electroencephalography Electrodes Alzheimer's disease Statistical analysis Feature extraction

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A hazmat transportation monitoring system based on Global Positioning System / Beidou Navigation Satellite System and RS485 bus

A hazmat transportation monitoring system based on Global Po...

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

作者： Yaoyao Xie Miao Yu Jie Fu Dong Chen Chengyun Yang College of Optoelectronic Engineering Chongqing University College of Mechaical Engineering Chongqing University Chongqing China

ISBN: (纸本)9781509037117

With the demand for road transport of hazmat in the past few years, accidents occur frequently during the dangerous goods transportation and road transportation safety issues become increasingly prominent. Therefore, it is urgent to make full use of technical measures of information collection and transmission to monitor the state of dangerous goods. A real-time system is put forward in this paper, which can monitor the state of hazmat during the transportation by using Global Positioning System (GPS)/BeiDou Navigation Satellite System (BDS) technology and sensor acquisition modules, which is based on RS485 bus technology. Combine the above technical schemes with General Packet Radio Service (GPRS) radio transmission, Radio Frequency Identification (RFID) and Geographic Information System (GIS) technology, the system can monitor the position information and crucial state information of the dangerous goods during the transportation. The system can fundamentally solve the safety issues of hazmat transport, and it is helpful to achieve scientific management in further.

关键词： Monitoring Hazardous materials Transportation Receivers Ground penetrating radar Global Positioning System Microprocessors

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A method to characterize and inspect the imprinting quality for a single dot in inkjet-printing

A method to characterize and inspect the imprinting quality ...

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

作者： Shuai Shao Yanfang Xu Yusheng Lian Zhimei Jia School of Printing & Packaging Engineering Beijing Institute of Graphic Communication Beijing China Beijing Nano Think Printing Technology co. Ltd Beijing China

ISBN: (纸本)9781509037117

To feature the location and morphology of inkjet printed dots, the printing quality characterizing and testing method of inkjet printed single dot is established. The digital single dot image of several tens of single dot on the square lattice point was designed. Then, the single dot image as the testing pattern was printed. The optical reflectivity of the testing pattern on micrometer-scale was acquired by the optical microscope, CCD capturing and optical calibration. The shape and location of each dot are determined with the optical reflectivity. The ideal coordinate distribution of the several tens of dots is derived from the statistical distribution of the measured values. The difference between the two mentioned distributions is used to represent the location accuracy of the dots. The area of dot and the parameters derived by elliptical fitting of the border of the dot are used to characterize the shape quality of dot. The method is applied to the inkjet printing plate process. The location accuracy of dot reached to the level of several micrometers. The diameter of the single dot is about 30 micrometers. The major axis of the fitting ellipse of dot has the certain statistical quality indicators. It indicates that the method can provide a general quantification characterization of the location and morphology quality of inkjet printed dots. This method can meet the demand of testing and analysis on the inkjet printing.

关键词： Ink Reflectivity Printing image color analysis Optical imaging Charge coupled devices

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Dynamic gene regulatory network-based inference framework for identifying cancer biomarkers

Dynamic gene regulatory network-based inference framework fo...

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

作者： Bo Yang Zheng Wu School of Computer Science and Engineering Xi'an Technological University Xi'an Shaanxi China College of Humanities Xi'an Technological University Xi'an Shaanxi China

ISBN: (纸本)9781509037117

Identification of reliable cancer biomarkers is a challenging task and great efforts have been devoted to utilize network-based methods to alleviate uncertainty of detected oncogenes. In the paper, an innovative network-based inference method is presented to recognize meaningful cancer-related genes. Firstly, a penalized kernel weighting algorithm is proposed, called ℓ2-norm regularized dynamic Smooth Network Reconstruction (lrSNR), which builds on radial basis function (RBF) kernel smoothing strategy and can be solved efficiently. Secondly, with the lrSNR, the gene regulatory network can be constructed from synthetic and real gene data. Thirdly, by ranking hub genes of the network and performing functional enrichment analysis, cancer biomarkers are obtained. Experimental results on man-made and real-world time series expression data reveal our proposed method significantly improves the computational accuracy and reliability in contrast with three competing methods (GlobalMIT, TSNI and NIR). Furthermore, the dynamic gene regulatory network-based inference schema can be extended to other complex diseases for discovery of disease associated-genes.

关键词： Heuristic algorithms Algorithm design and analysis Biology Kernel Inference algorithms Computational modeling Cancer

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Architectural distortion recognition based on a subclass technique and the sparse representation classifier

Architectural distortion recognition based on a subclass tec...

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

作者： Xiaoming Liu Leilei Zhai Ting Zhu Zhou Yang School of Automation Huazhong University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781509037117

Architectural distortion is the third most common sign of breast cancer in mammograms. The accurate recognition is important for computer aided diagnosis of breast cancer. However, due to the subtle symptom and complex structures in the mammogram images, it is difficult to recognize whether a region of interest (ROI) is truly an architectural distortion. In this paper, we proposed a new method for architectural distortion recognition. In the proposed method, several texture features are extracted for each region of interest, including features from GLCM matrix, spiculated related features, entropy features, etc. Feature selection is obtained by a sub-classes clustering based multi-task learning method (SMTL), which can utilize the discriminative label information and reflect the multi-clustering characteristic of the data samples. Finally, the powerful sparse representation based classifier is used for the classification of AD or non-AD. The proposed method has been tested on DDSM dataset and compared with several other methods, the experimental results showed the effectiveness of the proposed method.

关键词： Feature extraction Distortion Entropy Training Mammography Delta-sigma modulation Breast cancer

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Analyzing Occupational Stress Based On Inner Composition Alignment Algorithm

Analyzing Occupational Stress Based On Inner Composition Ali...

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

作者： Zhen Shi Shitong Wang Jun Wang Jiafei Dai Fengzhen Hou Jin Li Image Processing and Image Communications Key Lab Nanjing Univ. of Posts & Telecomm China Nanjing Brain Hospital China School of Science China Pharmaceutical University Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi'an China

ISBN: (纸本)9781509037117

To distinguish different level of occupational stress of students and nurses, this paper applied inner composition alignment (IOTA) algorithm to analyse differences between the students' Electroencephalogram (EEG) and the nurses' EEG and to explore the influence of occupational stress on EEG. First, we selected nine cases of students EEG data and the same quantity of nurses EEG data from General Hospital of Nanjing Military Region, then, constructed two different brain networks by utilizing IOTA method and analyzed the networks characteristics which include IOTA coefficient, Clustering coefficient and Average degree. In order to verify the accuracy of the results, we used SPSS to analyse the significant difference hypothesis testing. The IOTA coefficients are inconsistent between students' EEG and nurses' EEG. Compared with the students, nurses' brain network is more complex. The level of occupational stress of nurses is higher than students. The IOTA algorithm can significantly distinguish occupational stress between students and nurses, and all results demonstrated the validity of the algorithm.

关键词： Brain Network Occupational Stress EEG IOTA Complex Network

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An Efficient Clustering Algorithm for Trajectory Points in Digital Movies Mobile Playing Systems

An Efficient Clustering Algorithm for Trajectory Points in D...

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

作者： Chunmei Zhang Xinfeng Zhang Enchang Sun Mingyu Wang Zhaoting Huang Feifei AN College of Electronic and Control Engineering Beijing University of Technology China Digital Program Management Center State Administration of Radio Film and Television Beijing China

ISBN: (纸本)9781509037117

In the paper, an efficient spatial clustering algorithm, the improved DBSCAN (Density Based Spatial Clustering of Applications with Noise), is proposed, for cluster analysis of trajectory points gathered from Digital Movies Mobile Playing Systems(DMSs). By searching the density of points which are greater than a given threshold in rural areas, the density-reachable maximum movie playing clusters are established. Moreover, the improved DBSCAN algorithm is based on the adjacent list structure to save space and time resources. The paper also adopts the real mobile projection GPS data in a province to analyze the clusters of movie trajectory points. Experiment results show that the presented algorithm can not only reflect quickly the overall distribution of the projection location information, but dig out the projection regions with high density. And the conclusions drawn from the paper are valuable for the management department to evaluate the tasks of the projectionists.

关键词： DBSCAN DMSs mobile projection trajectory points density clustering adjacent list

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Design of the Portable Instrument for Bioelectrical Impedance

Design of the Portable Instrument for Bioelectrical Impedanc...

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

作者： Bo Chen Xiu-e Gao Jinfeng Wu Qingguo Zheng College of Information Engineering Dalian University

ISBN: (纸本)9781509037117

Bioelectrical impedance is a body's important parameter, which, to a certain degree, reflects the physiological state of the human body. According to the shortage that traditional five-segments model of human body impedance can't satisfy the needs of figuring out human trunk subdivision impedance, the exiting solution of eight-segments bioelectrical impedance module is premised on the basis of symmetrical limbs (symmetrical limbs is not existed in fact).Therefore, an asymmetrical model for measuring the impedance of eight-segments of human body is proposed, two solving equations are used to supplement the impedance relation of the left and right upper limbs and the impedance of the left and right lower limbs by using the five-segments impedance model, solving the problem in the asymmetric eight-segments impedance model, where the resistance is hard to work out. Based on this theory, a portable eight-segments body impedance instrument is designed, an integral design of this instrument is introduced and a contrast experiment with the InBody770 instrument is designed. The results show that the accuracy of the measuring instrument is close to the InBody770 instrument, which meets the needs of measuring the subdivision impedance in human trunk part.

关键词： measuring instrument asymmetric eight-segments model bioelectrical impedance

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The correlation analysis of muscle fatigue degree of flexor carpi radialis and mechanomyographic frequency-domain features

The correlation analysis of muscle fatigue degree of flexor ...

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

作者： Yue Zhang Chun-Ming Xia Hao Zhong Xiao-Lin Gu Tao Xie School of Mechanical and Power Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9781509037117

In this study, mechanomyography (MMG) was used to evaluate the effectiveness and sensibility of the degree of muscle fatigue. The preprocessed MMG signal was decomposed by 6-scale discrete wavelet transform (DWT) to acquire the coefficients of each scale. The coefficients of low frequency of scale 3, 4, 5 (A3, A4, A5) were used to reconstruct signals respectively. Frequency-domain features were extracted, and linear regression equations were established to make comparisons, which indicated that 15-62Hz frequency bands play a major role in that frequency spectrum shifting to lower frequencies. To learn more information, the MMG signal was processed by 6-layer wavelet packet decomposition (WPD), and the coefficients of each node were acquired. The coefficients of 6 nodes (ADAAAA6, DDAAAA6, AADAAA6, DADAAA6, ADDAAA6, DDDAAA6) were selected to reconstruct signals. The change of power of reconstructed signals during muscle fatigue were calculated and compared. The results suggested that power of MMG was decreasing and 31-54 Hz frequency band showed more sensitivity to muscle fatigue induced by static exertion.

关键词： Muscles Fatigue Discrete wavelet transforms Frequency-domain analysis Feature extraction Wavelet packets Electromyography

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