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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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Distance Selection for image Super-Resolution by Dictionary Optimization 9

Distance Selection for Image Super-Resolution by Dictionary ...

引用

9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhang, Jianguang Li, Yongxia Li, Jing Liu, Baoying Hengshui Univ Dept Math & Comp Sci Hengshui 053000 Peoples R China Hengshui Univ Off Educ Adm Hengshui 053000 Peoples R China Tianjin Univ Sci & Technol Coll Elect Informat & Automat Tianjin 300222 Peoples R China Hengshui Univ Dept Polit Sci & Law Hengshui 053000 Peoples R China

ISBN: (纸本)9781509037100

The quality of Learning-based super-resolution (SR) largely depends on whether the dictionary includes rich details which are strongly similar to the input image. In this paper, for each input image, we optimize the dictionary by selecting the most similar images based on the SIFT feature. A rich set of candidate distance metrics, such as Median distance, Euclidean distance, Harmonic distance and Geometric distance, are explored to match the SIFT feature, which can provide more accurate matching result than only using Euclidean distance. The optimal distance of each target image can be selected by comparing the four super-resolution images, which are recovered by using each distance metric. According the optimal distance metric, all target images are divided into three groups. We propose a novel bag-of-words (BOW) model for quantize the input image and target images, and then select the optimal distance of input image by finding the most similar target image. Experimental results demonstrate that our method can obtain the high hit rate and the select distance is more adaptive for input image than the traditional Euclidean distance.

关键词： Super-resolution Dictionary SIFT Distance metric BOW

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Research on Digitalized Design Technology of Teeth Shape Support Implant Guide Based on image Guide 9

Research on Digitalized Design Technology of Teeth Shape Sup...

引用

9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhong, Yicheng Dai, Ning Xing, Rui Cheng, Xiaosheng Sun, Yuchun Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing Jiangsu Peoples R China Peking Univ Sch Stomatol Beijing Peoples R China

ISBN: (纸本)9781509037100

This paper proposed a novel method for dental implant guide, based on computer aided design technique with CT data and dental 3D data. We analyze the patient's 3D dental data, and then plan the implant area and support area interactively. With the help of 2D image, we can accurately calculate the anatomical implants direction and a safe distance. With biomechanical principles as well as aesthetical and functional requirements as precondition, this method can make full use of the remaining teeth to ensure the support's stability. First of all, this method needs import and preprocess the model which needs repairing. Secondly, the implant direction was automatically computed. After that, the implant and support area was designed semi-automatically. Then, we design the dental platform and implant parametrically with the help of CT image registration. Finally, the dental implant guide is generated after Boolean operations. In the end of this paper, a case research explained the whole process of surgical guide. The results validated the correctness and feasibility of this method which has a great significance to enhance the quality and accuracy of implant surgery.

关键词： dental implantation surgical guide digital design 3D printer

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Self-adapting Threshold of Pulmonary Parenchyma 9

Self-adapting Threshold of Pulmonary Parenchyma

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Li, Xin-Yue Xu, Fan Hu, Xiao Peng, Shao-Hu Nam, Hyun-Do Zhao, Jin-Ming Guangzhou Univ Sch Mech & Elect Engn Guangzhou Guangdong Peoples R China Dankook Univ Dept Elect & Elect Engn Yongin South Korea Sun Yat Sen Univ Affiliated Hosp 6 Dept Thorac Surg Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781509037100

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

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Architectural Distortion Recognition based on a Subclass Technique and the Sparse Representation Classifier 9

Architectural Distortion Recognition based on a Subclass Tec...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Liu, Xiaoming Zhai, Leilei Zhu, Ting Yang, Zhou Huazhong Univ Sci & Technol Sch Automat Wuhan Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Wuhan Univ Sci & Technol Coll Comp Sci & Technol Wuhan Peoples R China Hubei Prov Key Lab Intelligent Informat Proc & Re Wuhan Peoples R China

ISBN: (纸本)9781509037100

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 multiclustering 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： Breast cancer Architectural distortion Sparse representation classifier Multi-task learning Computer aided detection

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A point matching algorithm for point set registration 9

A point matching algorithm for point set registration

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9th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2016

作者： Huang, Yan Umulis, David M. Agricultural and Biological Engineering West LafayetteIN47907 United States Weldon School of Biomedical Engineering West LafayetteIN47907 United States

ISBN: (纸本)9781509037100

Point cloud data sets, or simply point clouds (PCs), originating from a common specimen but containing different measurement parameters (i.e. using different sensors, times, depths, viewpoints, etc.) usually contain both overlapping and non-overlapping points. Registration aligns these distinct PCs into one coordinate system by assigning point-by-point correspondence between PCs and applying a transformation. Registration shows great potential in practical applications, but the effectiveness of current methods is limited in PCs having large differences in relative initial positions, low overlapping ratios, and excessive noise. We introduce a point matching algorithm called Signature that relaxes these constraints. We approach the problem of identifying corresponding points between PCs by assigning and matching point identification (ID), or the distance of a point to a select number of closest points in the same PC. Signature has been tested on PCs generated computationally and by fluorescence imaging of biological samples. Signature accurately identifies point correspondence in PCs with any initial angles, with overlapping ratios as low as 15%. Preprocessing with Signature intelligently relaxes constraints on initial positions and overlapping ratios and shows some improvement in aligning noisy PCs for both point-wise and topological registration methods. Furthermore, combining Signature with Anchor Point Alignment allows for robust alignment of noise-free PCs under any initial position. © 2016 IEEE.

关键词： Fluorescence imaging

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Analyzing Occupational Stress Based On Inner Composition Alignment Algorithm 9

Analyzing Occupational Stress Based On Inner Composition Ali...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Shi, Zhen Wang, Shitong Wang, Jun Dai, Jiafei Hou, Fengzhen Li, Jin Nanjing Univ Posts & Telecomm Image Proc & Image Commun Key Lab Nanjing Jiangsu Peoples R China Nanjing Brain Hosp Nanjing Jiangsu Peoples R China China Pharmaceut Univ Sch Sci Nanjing Jiangsu Peoples R China Shaanxi Normal Univ Coll Phys & Informat Technol Xian Peoples R China

ISBN: (纸本)9781509037100

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： Occupational Stress EEG IOTA Complex Network Brain Network

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Analysis of Multiscale Sign Series Entropy of the Young and Middle-aged Electroencephalogram signals 9

Analysis of Multiscale Sign Series Entropy of the Young and ...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Du, Fei Wang, Shitong Wang, Jun Dai, Jiafei Hou, Fengzhen Li, Jin Nanjing Univ Posts & Telecomm Image Proc & Image Commun Key Lab Nanjing Jiangsu Peoples R China Nanjing Gen Hosp Nanjing Mil Command Nanjing Jiangsu Peoples R China China Pharmaceut Univ Sch Sci Nanjing Jiangsu Peoples R China Shaanxi Normal Univ Coll Phys & Informat Technol Xian Peoples R China

ISBN: (纸本)9781509037100

The physiological analysis of electroencephalogram (EEG) signals is of great significance in assessing the activity of the brain function and the physiological state. EEG is a means of clinical examination of brain diseases. Age is one of the important factors that affect the results of the EEG. EEG signal analysis is mainly to analyze the time series of the signal, multiscale entropy (MSE) analysis [1-3] is the method that used to analyze the finite length of the time series. Multiscale sign series entropy (MSSE) method is proposed for the analysis of EEG signals in the young and middle-aged. We use the proposed method to analyze the signals from several aspects of data length, word length, noise, multi scale etc. By analyzing the influence of these factors, we can still distinguish the EEG signals of different ages. Multiscale sign series entropy (MSSE) analysis algorithm can effectively separate the brain electrical signals from the young and middle aged, which is expected to have a certain reference value for the traditional pathological analysis of the EEG signals.

关键词： EEG the young and middle-aged EEG sign series entropy (SSE) multi-scale sign series entropy(MSSE)

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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 9

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

引用

9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Xu, Yingying Lin, Lanfen Hu, Hongjie Wang, Dan Liu, Yitao Wang, Jian Han, Xianhua Chen, Yen-Wei Zhejiang Univ Coll Comp Sci & Technol Hangzhou Zhejiang Peoples R China Sir Run Run Shaw Hosp Dept Radiol Hangzhou Zhejiang Peoples R China Ritsumeikan Univ Grad Sch Sci & Engn Shiga Japan

ISBN: (纸本)9781509037100

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

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Remote and Collaborative Medical image Visualization Computing Platform 9

Remote and Collaborative Medical Image Visualization Computi...

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9th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Deng, Zhuofu Zhu, Zhiliang Chen, Yen-Wei Northeastern Univ Coll Software Engn Shenyang Peoples R China Ritsumeikan Univ Coll Informat Sci & Engn Kusatsu Shiga Japan

ISBN: (纸本)9781509037100

With the development of computing capability and display size in computing hardware, mobile terminals like iPhone or iPad have been more and more accepted as a tool to help radiologists to examine medical images of patients in order to give more accurate diagnostic conclusion through server. The radiologists can observe the images by interacting them with different hand gestures to translate, rotate and zoom in or out the objects in the medical images of the mobile terminals. However, because of the requirements of remote medical, we need a system that should have one kind of function-collaboration, which means that when different radiologists located at different places hold a remote teleconference to discuss the same medical images for difficult miscellaneous disease, one expert wishes that when he changes the position of object in the images the other experts will see the changes at once so that they can keep accordance all the time to talk over the focus with voice communication and other auxiliary tools. This paper developed a remote and collaborative medical image visualization system where medical experts can work collaboratively with each other. In the proposed application, the server system can file the data of patients like CT, MR images and other information. Meanwhile, the terminal clients can download the medical 2D data and rendering them on itself including 3D image reconstruction, moreover the server can also support teleconference mode that the experts in different places discuss one patient's illness with this system like in the same location of conference. Finally, the performance issues regarding the remote 3D visualization of the medical images platform over the wireless network of the proposed system were also discussed. The result demonstrated that the proposed remote and collaborative medical image visualization computing platform could provide a perfect interactive experience in the WLAN and 4G network.

关键词： remote medical Collaborative visualizaton platform 3D reconstruction

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MIMO radar arrays optimization analysis

MIMO radar arrays optimization analysis

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

作者： Qiang Wei Hongbo Xu Zhong Liu Air Force Early Warning Academy Wuhan China Electronics Engineering College Naval University of Engineering Wuhan China

ISBN: (纸本)9781509037117

Aiming at the problem about MIMO radar arrays, this paper analylizes the problem by the probability of detection. Some detection models are deduced, and a simulation flow is designed. Simulations are carried out based on different system configurations, and an optimization suggestion is obtained about antenna element numbers of long baseline MIMO radar.

关键词： MIMO radar Radar antennas Transmitters Receivers MIMO Antenna arrays

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