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Iranian Conference on electrical engineering (ICEE)

作者： Maryam Afzali Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

ISBN: (纸本)9781424467600

Temporal lobe epilepsy (TLE) is a neurological disease that affects millions of individuals in the world. Majority of TLE patients suffer from refractory seizures. Determining abnormal/damaged regions of the brain that harbor seizure focus is a critical step towards treatment of TLE patients. Diffusion tensor imaging (DTI) is a non-invasive method that we use in this work to determine damaged regions of white matter in the brain. To this end, we apply two methods, voxel based morphometry (VBM) and fiber tracking. We use these methods along with two anisotropy maps (EAR and FA) extracted from the DTI data. We use DTI data of 31 subjects (12 normal subjects and 19 TLE patients) for testing and evaluation studies. The VBM method shows that TLE is associated with reduction of both of FA and EAR values in several regions within the temporal lobes. The tractography method shows abnormal diffusion characteristics in three fiber bundles (fornix, uncinate fasciculus, and cingulum). The results show that the EAR maps are less sensitive to noise than the FA maps and the EAR values change more than the FA values in TLE.

关键词： Tensile stress Magnetic resonance imaging Diffusion tensor imaging Temporal lobe Epilepsy Ear Optical fiber testing Diseases Focusing Medical treatment

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A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation

A statistical shape model using 2D-principal component analy...

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International Conference on Software engineering and Data Mining (SEDM)

作者： Tomoko Tateyama Taishi Tanaka Shinya Kohara Amir Hossein Foruzan Akira Furukawa Yen-Wei Chen Intelligent Image Processing Laboratory College of Information Science and Engineering Ritsumeikan University Shiga Japan Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Radiology Shiga University of Medical Science Shiga Japan

ISBN: (纸本)9781424473243;9788988678220;9788988678213

Since the medical training samples are very limited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good generalization even using fewer samples.

关键词： Biomedical imaging Shape control Biomedical engineering Principal component analysis Liver Information analysis Educational institutions Azimuth Covariance matrix image analysis

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Multiple-atlas-based automatic sementation of hippocampus for lateralization in temporal lobe epilepsy

Multiple-atlas-based automatic sementation of hippocampus fo...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi-Asl Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Image Analysis Laboratory Department of Diagnostic Radiology Henry Ford Health System Detroit MI USA School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259

We introduce a 3D segmentation framework which uses principal shapes. The probabilistic energy function of the method is defined based on intensity, tissue type, and location information of the structures using a multiple atlas method. For intensity information, nonparametric probability density function is used which considers intensity relation of different structures. To find a local minimum of the energy function, a two-step optimization strategy is used. In the first step, shape parameters are optimized based on the analytic derivatives of the energy function. In the second step, shapes of the structures are fine-tuned using a level set method. The proposed method is shown to be superior to some popular methods in the literature using a dataset of 64 patients with mesial temporal lobe epilepsy. In addition, the method can be used for lateralization with accuracy close to that of manual segmentation.

关键词： Hippocampus Temporal lobe Epilepsy image segmentation Principal component analysis Shape control Probability density function Level set Skull Algorithm design and analysis

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Volume-based Magnetic Resonance Brain image Classification

Volume-based Magnetic Resonance Brain Image Classification

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International Conference on Genetic and Evolutionary Computing (ICGEC)

作者： Yaw-Jiunn Chiou Jyh-Wen Chai Clayton Chi-Chang Chen Shih-Yu Chen Hsian-Min Chen Yen-Chieh Ouyang Wu-Chung Su Ching Tsorng Tsai Ching-Wen Yang San-Kan Lee Chein-I Chang Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Section of Radiology College of Medicine China Medical University Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung Taiwan Department of Biomedical Engineering Hungkuang University Taichung Taiwan Computer Science Department Tunghai University Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

This paper develops a volume-based technique, called Volume Sphering Analysis (VSA) which can process all acquired Magnetic Resonance (MR) image slices formed image cube using only one set of training samples obtained from an image slice. So, several significant advantages and benefits can be gained from our proposed VSA. In the past, when MR image classification is performed, each image slice requires its own specific training samples and training samples obtained from one slice are not applied to another slice. The VSA allows users to reduce computational time. In addition, it saves significant effort in selecting training samples for each of image slices. Thirdly, it is robust to all image slices compared to the traditional one-slice MR image classification which is sensitive to each image slice. Experimental results demonstrate that the VSA performs as well as does that using specifically selected training samples for individual image slices.

关键词： Training Support vector machine classification image classification Vectors Volume measurement Magnetic resonance

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Testing Cross-Platform Streaming of Video Games over Wired and Wireless LANs

Testing Cross-Platform Streaming of Video Games over Wired a...

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International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Audrius Jurgelionis Francesco Bellotti Alessandro De Gloria Jukka-Pekka Laulajainen Philipp Fechteler Peter Eisert Haggai David Department of Biophysical and Electronic Engineering University of Genoa Genoa Italy Universita degli Studi di Genova Genova Liguria IT Converging Networks Laboratory VTT Technical Research Center of Finland Oulu Finland Computer Vision & Graphics Fraunhofer-Institute for Telecommunications Berlin Germany Computer Vision & Graphics Image Processing Department Heinrich-Hertz-Institute Fraunhofer Institute of Telecommunications Berlin Germany Converging Networks Laboratory VTT Technical Research Centre of Finland Oulu Finland R&D Department Exent Technologies Ltd. Petach Tikva Israel

In this paper we present a new cross-platform approach for video game delivery in wired and wireless local networks. The developed 3D streaming and video streaming approaches enable users to access video games on set top boxes and handheld devices that natively are not capable to run PC games. During the development of the distributed gaming system we have faced a number of challenges and problems posed by the hardware and network limitations. In order to solve these problems we have developed a multilevel testing methodology which is based on user assessment and technical measures for the system under development. In this paper we focus on the technical measures and instrumentation that we use for the system's performance measurement and testing. The benefits of our testing methodology are demonstrated through examples from the development and testing work.

关键词： Streaming media Games Wireless LAN System testing computer graphics Hardware Cloud computing Delay image coding computer architecture

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Restoration of out of focus barcode images using Wiener filter

Restoration of out of focus barcode images using Wiener filt...

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5th International Conference on Signal-image Technology and Internet-Based Systems, SITIS 2009

作者： Addiati, D. Sheikh, U.U. Abu Bakar, S.A.R. Computer Vision Video and Image Processing Laboratory Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Skudai Malaysia

ISBN: (纸本)9780769539591

Barcode capturing using embedded camera in mobile phone is prone to producing images with out of focus blurring. Barcode decoding systems usually fail to decode barcodes from an image that is affected by image blurring. With macro function, users are able to capture sharp barcodes. Unfortunately, low end and mid range cameras usually do not have macro function which enables close range image capturing. To improve barcode recognition, we propose a technique to restore barcode images before the decoding process. First, we identify and calculate the point spread function (PSF) parameter and radius of the blur in Cepstrum domain. Then we restore the degraded image using Wiener filter. Experiments on both synthetic and real images show that our technique is adept in estimating the radius of the blur. The Wiener filter gives satisfactory result when it is used to restore blurred images with the acquired PSF from the preceding step. © 2009 IEEE.

关键词： image reconstruction

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Techniques for Automatic Magnetic Resonance image Classification

Techniques for Automatic Magnetic Resonance Image Classifica...

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International Conference on Genetic and Evolutionary Computing (ICGEC)

作者： Hsian-Min Chen Shih-Yu Chen Jyh Wen Chai Clayton Chi-Chang Chen Chao-Cheng Wu Yen-Chieh Ouyang Ching Tsorng Tsai Ching-Wen Yang San-Kan Lee Chein-I Chang Department of Biomedical Engineering Hungkuang University Taichung Taiwan Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Section of Radiology College of Medicine China Medical University Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Computer Science Department Tunghai University Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Designing and developing automatic techniques for magnetic resonance images (MR) for data analysis is very challenging. One popular and public available method, FAST (FMRIB Automatic Segmentation Tool) has been widely used for automatic brain tissue segmentation for this purpose. This paper investigates limitations of this software algorithm on implementation and further develops a new approach to automatic MR brain tissue classification. The proposed new technique first implements an unsupervised training sample generation process (UTSGP) which includes a Pixel Purity Index (PPI) to generate an initial set of training samples that are further refined by a Support Vector Machine. The resulting training samples are then as a set of training samples for an Iterative Fisher's Linear Discriminant Analysis (IFLDA) which implements FLDA iteratively to improve classification. In order to conduct a fair comparison synthetic images are used for performance evaluation. Experimental results show that our proposed technique is superior in practical implementation to this software algorithm in several aspects of generalization ability, flexibility of choosing number of classes to be classified, avoidance of inconsistent results caused by different initial conditions.

关键词： Classification algorithms Training image segmentation Brain Skull Software algorithms Support vector machines

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Improved rice algorithm of lossless compression for on-board images

Improved rice algorithm of lossless compression for on-board...

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International Conference on Multimedia Technology

作者： Wei, Yong-Wang Ding, Qing-Hai Luo, Hai-Bo Shenyang Institute of Automation Chinese Academy of Science Shenyang 110016 China Graduate School of Chinese Academy of Science Beijing 100049 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province 110016 China Electrical and Information Engineering College Beihua University Jilin 132021 China Research Institute of General Development and Demonstration of Equipment Equipment Academy of Air Force Beijing100076 China

ISBN: (纸本)9781424478743

Aiming at the problems of the relatively lower compression ratio and the difficulty in hardware implementation regarding Rice lossless compression algorithm for the Space-borne Remote-sensing images, an improved Rice method is proposed in which the length of predictor FIFO is determined by the size of input images and the global unicode for differences is used. The improved Rice algorithm is mainly composed of two steps, MED prediction for the whole row data and Rice global uniform entropy coding. The statistical results show that it can significantly reduce the spatial redundancy of the adjacent pixels and the mean value of image differences. The compression bit rate is reduced approximately 0.4581 bpp(bit/pixel) against the original Rice algorithm. Furthermore, the new way reserves the all detail information of the input images throughout the whole encoding process. Because we split the all samples with the same mode, the proportion of the identifier of the splitting mechanic in the output data stream is reduced and the compression ratio is increased. The improvement can reduce the encoding complexity and be easily implemented for hardware application. ©2010 IEEE.

关键词： Signal encoding

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Critical motion detection of nearby moving vehicles in a vision-based driver-assistance system

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IEEE Transactions on Intelligent Transportation Systems 2009年第1期10卷 70-82页

作者： Cherng, Shen Fang, Chiung-Yao Chen, Chia-Pei Chen, Sei-Wang Department of Computer Science and Information Engineering Chengshiu University Kaohsiung 833 Taiwan Laboratory for Computer Vision and Image Processing Department of Computer Science and Information Engineering National Taiwan Normal University Taipei 116 Taiwan Chunghwa Telecom Laboratories Taoyuan 32617 Taiwan

Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized. A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system. © 2006 IEEE.

关键词： Motion analysis

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Inpainting in shape from focus: Taking a cue from motion parallax

Inpainting in shape from focus: Taking a cue from motion par...

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2009 20th British Machine vision Conference, BMVC 2009

作者： Sahay, Rajiv R. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering Indian Institute of Technology Madras Chennai 600 036 India

ISBN: (纸本)1901725391

Shape from focus (SFF) which uses a sequence of space-variantly defocused frames works under the constraint that there is 'no magnification' in the stack. In the presence of sensor damage and/or occlusions, there will be missing data in the observations and SFF cannot recover structure in those regions. In many applications, the capability of filling-in missing data is of critical importance. In this paper, we investigate the effect of motion parallax in SFF and demonstrate the interesting possibility of how it can be judiciously used to jointly inpaint image and depth profiles. When there is relative motion between the 3D specimen and the camera, by virtue of the inherent pixel motion in each of the frames, it is possible to obtain a focused image and depth map of the scene despite missing regions in the observations. © 2009. The copyright of this document resides with its authors.

关键词： Geometrical optics

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