检索结果-内蒙古大学图书馆

Computers in Cardiology (CinC)

作者： Wei Song Xin Yang Jing Wang Yi Yu Sun Kun Institution of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Shanghai Childrens Medical Center Medical College Shanghai Jiaotong University Shanghai China Xinhua Hospital School of Medicine Shanghai Jiaotong University Shanghai China

In order to assist diagnosis and surgical repair of congenital mitral disease, quantitative analysis of 3D geometry of the mitral complex is necessary for better understanding mechanism and dysfunction of the mitral complex. This work aims to extract geometric parameters of mitral complex and utilize Support Vector Machines (SVM) based classifier to support diagnosis of congenital mitral regurgitation (MR). With a control group of 20 normal young children (11 boys, 9 girls, 5.96±3.12 years) with normal structure of mitral apparatus, 20 patients (9 boys, 11 girls, 5.59±3.30 years) suffering from severe congenital MR are recruited in this study. The results of parameter validation demonstrates that the measurement precision is in the range of inter-/intra-observer variability. SVM-based classifier achieves average classification accuracy at 85.0% in the present population.

关键词： Muscles Support vector machines Three dimensional displays Geometry Pediatrics Valves Educational institutions

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Predicting functional impact of single amino acid polymorphisms by integrating sequence and structural features

Predicting functional impact of single amino acid polymorphi...

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IEEE International Conference on Systems Biology

作者： Mingjun Wang Hong-Bin Shen Tatsuya Akutsu Jiangning Song State Engineering Laboratory for Industrial Enzymes Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences (CAS) Tianjin China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Department of Biochemistry and Molecular Biology Faculty of Medicine Monash University Melbourne VIC Australia

Single amino acid polymorphisms (SAPs) are the most abundant form of known genetic variations associated with human diseases. It is of great interest to study the sequence-structure-function relationship underlying SAPs. In this work, we collected the human variant data from three databases and divided them into three categories, i.e. cancer somatic mutations (CSM), Mendelian disease-related variant (SVD) and neutral polymorphisms (SVP). We built support vector machine (SVM) classifiers to predict these three classes of SAPs, using the optimal features selected by a random forest algorithm. Consequently, 280 sequence-derived and structural features were initially extracted from the curated datasets from which 18 optimal candidate features were further selected by random forest. Furthermore, we performed a stepwise feature selection to select characteristic sequence and structural features that are important for predicting each SAPs class. As a result, our predictors achieved a prediction accuracy (ACC) of 84.97, 96.93, 86.98 and 88.24%, for the three classes, CSM, SVD and SVP, respectively. Performance comparison with other previously developed tools such as SIFT, SNAP and Polyphen2 indicates that our method provides a favorable performance with higher Sensitivity scores and Matthew's correlation coefficients (MCC). These results indicate that the prediction performance of SAPs classifiers can be effectively improved by feature selection. Moreover, division of SAPs into three respective categories and construction of accurate SVM-based classifiers for each class provides a practically useful way for investigating the difference between Mendelian disease-related variants and cancer somatic mutations.

关键词： Support vector machines Accuracy Proteins Feature extraction Humans Amino acids Databases

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Interactive object extraction using hierarchical graph cuts

Interactive object extraction using hierarchical graph cuts

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2010 International Conference on Audio, Language and image processing, ICALIP 2010

作者： Zhang, Yan Song, Haohao Gu, Jian Yu, Shengyang Yang, Jie Third Research Institute of Ministry of Public Security Shanghai 200031 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9781424458653

Foreground object extraction, which aims to accurately separate a foreground object from its background in still images, plays an important role in many computer vision applications. An interactive object extraction method by extending the graph cut approach is presented in this paper. The coarse-to-fine object segmentation method makes it efficiently to specify the main object and adjust the detail of object. The user interaction is simplified to drawing a rectangle around the desired object, followed by optional boundary editing. The coarse scale segmentation is performed on the basis of the initial interactive rectangle, the accurate boundary portrayal is performed at the finer scale. A pyramid structure provides a framework for the processing, and this hierarchical structure ensures rapid boundary mapping between pyramid levels. Experimental results on multiple kinds of color images show the effectiveness and convenience of the approach. ©2010 IEEE.

关键词： Extraction

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Registration-based auto-detection of the optimal cross sections in 3D echocardiographic images

Registration-based auto-detection of the optimal cross secti...

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2010 International Conference on Bioinformatics and Biomedical Technology, ICBBT 2010

作者： Liu, Xiaoping Yang, Xin Wu, Lanping Tan, Xiao Computer Center East China Normal University Shanghai China Institute of Pattern Recognition and Image Processing Shanghai Jiaotong University Shanghai China Childerns' Medical Center Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424467761

In most cases, echocardiographers examine threedimensional (3D) or four-dimensional (4D) echocardiographic images by studying several important cross sections which are defined as the optimal cross sections. It is a time-consuming and tedious task for echocardiographers to manually search the optimal cross sections by existing real-time 3D echocardiography (RT3DE) systems or off-line 3D softwares. To assist doctors' diagnosis, we design a registration-based method to automatically detect the optimal cross sections in three-dimensional echocardiographic (3DE) images. Firstly, a normal end-diastolic (ED) volumetric data is chosen, in which its optimal cross section is predetermined. Secondly, instead of the whole ED volume, only part of it is selected as the template. Finally, all the optimal cross sections of a 3DE image are detected by aligning the 3DE image with the template image. As a preliminary study, we performed this method on 28 normal apical datasets and the error rate is 15%. The results show good prospects for implementing automatic detection, which might offer better repeatability and save time. Furthermore, it can be a prior procedure for measurement and the computer-aided diagnosis. © 2010 IEEE.

关键词： Echocardiography

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Ethnicity classification based on gait using multi-view fusion

Ethnicity classification based on gait using multi-view fusi...

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2010 IEEE Computer Society Conference on Computer Vision and pattern recognition - Workshops, CVPRW 2010

作者： Zhang, De Wang, Yunhong Bhanu, Bir Intelligent Recognition and Image Processing Laboratory Beihang University Beijing 100191 China Center for Research in Intelligent Systems University of California Riverside CA 92521 United States

ISBN: (纸本)9781424470297

The determination of ethnicity of an individual, as a soft biometrics, can be very useful in a video-based surveillance system. Currently, face is commonly used to determine the ethnicity of a person. Up to now, gait has been used for individual recognition and gender classification but not for ethnicity determination. This paper focuses on the ethnicity determination based on fusion of multi-view gait. Gait Energy image (GEI) is used to analyze the recognition power of gait for ethnicity. Feature fusion, score fusion and decision fusion from multiple views of gait are explored. For the feature fusion, GEI images and camera views are put together to render a third-order tensor (x;y;view). A multilinear principal component analysis (MPCA) is used to extract features from tensor objects which integrate all views. For the score fusion, the similarity scores measured from single views are combined with a weighted SUM rule. For the decision fusion, ethnicity classification is realized on each individual view first. The classification results are then combined to make the final determination with a majority vote rule. A database of 36 walking people (East Asian and South American) was acquired from 7 different camera views. The experimental results show that ethnicity can be determined from human gait in video automatically. The classification rate is improved by fusing multiple camera views and a comparison among different fusion schemes shows that the MPCA based feature fusion performs thebest. © 2010 IEEE.

关键词： Principal component analysis

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Age classification based on gait using HMM

Age classification based on gait using HMM

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2010 20th International Conference on pattern recognition, ICPR 2010

作者： Zhang, De Wang, Yunhong Bhanu, Bir Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100191 China Center for Research in Intelligent Systems University of California Riverside CA 92521 United States

ISBN: (纸本)9780769541099

In this paper we propose a new framework for age classification based on human gait using Hidden Markov Model (HMM). A gait database including young people and elderly people is built. To extract appropriate gait features, we consider a contour related method in terms of shape variations during human walking. Then the image feature is transformed to a lower-dimensional space by using the Frame to Exemplar (FED) distance. A HMM is trained on the FED vector sequences. Thus, the framework provides flexibility in the selection of gait feature representation. In addition, the framework is robust for classification due to the statistical nature of HMM. The experimental results show that video-based automatic age classification from human gait is feasible and reliable. © 2010 IEEE.

关键词： Hidden Markov models

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Three-dimensional ultrasonic data smooth and endocardial extraction

Three-dimensional ultrasonic data smooth and endocardial ext...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Xionghu Luo Huilin Xiong Guozhen Chen Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Heart Center Shanghai Children's Medical Center Shanghai China

This paper presents a new approach for visualizing the surfaces from 3D ultrasound data. 3D ultrasound data usually contain substantial quantity of speckle noise, which makes the extraction of smooth and continuous surfaces extremely difficult. In this paper, combining the partial differential equation model of anisotropic diffusion filter with the Lee filter, we present a new algorithm for handling 3D ultrasound data, aiming to suppress the speckle noise, and meanwhile, smooth the ultrasound image. Additionally, the marching cubes algorithm is applied to extract a smooth endocardial surface. Comparing experiments are presented to illustrate the effectiveness of our approach.

关键词： Noise Mathematical model Anisotropic magnetoresistance Three dimensional displays Speckle Rendering (computer graphics) Filtering algorithms

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Interactive Object Extraction Using Hierarchical Graph Cuts

Interactive Object Extraction Using Hierarchical Graph Cuts

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2010 International Conference on Audio,Language and image processing(2010年音频、语言与图像处理国际会议 ICALIP 2010)

作者： Jian Gu Haohao Song Yan Zhang Jie Yang Shengyang Yu The Third Research Institute of Ministry of Public Security Shanghai 200031 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240

ISBN: (纸本)9781424458653

Foreground object extraction, which aims to accurately separate a foreground object from its background in still images, plays an important role in many computer vision applications. An interactive object extraction method by extending the graph cut approach is presented in this paper. The coarse-tofine object segmentation method makes it efficiently to specify the main object and adjust the detail of object. The user interaction is simplified to drawing a rectangle around the desired object, followed by optional boundary editing. The coarse scale segmentation is performed on the basis of the initial interactive rectangle, the accurate boundary portrayal is performed at the finer scale. A pyramid structure provides a framework for the processing, and this hierarchical structure ensures rapid boundary mapping between pyramid levels. Experimental results on multiple kinds of color images show the effectiveness and convenience of the approach.

关键词： extraction of object Still images Interactive user-computer interaction color image Rectangle images computer vision Line graph

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DSA image registration based on 3D space-time detection

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Procedia Engineering 2010年 7卷 426-431页

作者： Xinhong Zhang Fan Zhang Rui Li Computing Center Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China

An image registration algorithm of digital subtraction angiography (DSA) is proposed based on 3D space-time detection. The DSA image sequence is considered as a 3D space-time sequence. In DSA image sequence, the movement of image points is detected for the control points selection and image registration. If the control points allocate in the blood vessels, their gray value will change obviously in the 3D space-time sequence. According to the location of control points, 3D space-time characteristics are used to select control points. Experimental results show that proposed scheme has a good performance in DSA image registration.

关键词： Digital subtraction angiography image registration 3D space-time detection

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Discovering structural regularity in facade image

Discovering structural regularity in facade image

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IEEE International Conference on Systems, Man and Cybernetics

作者： Weiwei Li Xin Zheng Jie Chen Image Processing and Pattern Recognition College of Information Science and Technology Beijing Normal University Beijing China Information Center CITIC Guoan Group Beijing China

3D reconstruction from single view is a very difficult problem in computer vision and computer graphics. Few works have been done in this area. In this paper, we proposed a method to discover structural regularity in single facade images on the procedural modeling of buildings by using SIFT algorithm. Firstly, symmetry information is detected from the image using SIFT algorithm for image analysis. Next, the symmetry information will be removed from the facade image. Finally, get the SIFT feature of widows and doors. Experiments show that our method can successfully discover regular structures with a higher recognition rate than existing method especially amidst shadowing and the changing illumination environment.

关键词： Laboratories

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