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Sixth International Conference on Intelligent Systems Design and Applications (ISDA 2006), vol.2

作者： XiuYing Wang Cherry Ballangan David Feng Biomedical and Multimedia Information Technology BMIT Group School of Information Technologies J12 University of Sydney NSW Australia Center of Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China

Biomedical image registration plays an important role in the intelligent use of large amount of medical data to establish safe healthcare. One of main challenges in abdominal image registration is to deal with elastic deformations caused by the shape and volume changes of internal organs, as well as heartbeat and breath. Other challenges include high computational efficiency required for clinical applications and accurate registration for 3D multimodality images. In this paper, an elastic, efficient and automatic 3D abdominal image registration method is proposed. Our proposed algorithm is divided into two stages and applied to register slice pairs of 3D volume data. First, non-iterative affine registration is performed to fix the global deformation by minimizing mean squared error (MSE). Then, effective active contour-based elastic registration is performed to correct the local deformations. This method has been validated by the experiments on both 3D CT-CT registration and CT-PET registration.

关键词： Abdomen Image registration Biomedical imaging Information technology Medical diagnostic imaging Medical services Registers Image sensors Diseases Intelligent sensors

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METHODS FOR IMPROVING RELIABILITY OF GLLS FOR PARAMETRIC IMAGE GENERATION

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IFAC Proceedings Volumes 2006年第18期39卷 237-241页

作者： Hon-Chit Choi Lingfeng Wen Stefan Eberl Dagan Feng Biomedical and Multimedia Information Technology (BMIT) Group School of Information Technologies University of Sydney Sydney Australia PET and Nuclear Medicine Dept. Royal Prince Alfred Hospital Sydney Australia Center for Multimedia Signal Processing Department of Electronic and Information Engineering the Hong Kong Polytechnic University Hong Kong

The computationally efficient generalized linear least square (GLLS) algorithm has been successfully applied in positron emission tomography (PET) for constructing parametric images from dynamic data. Recently, we have applied GLLS to substantially more noisy single photon emission computed tomography (SPECT) data. Due to the nature of the data, GLLS sometimes failed to provide physiologically meaningful estimates. In this work, we investigated two potential methods to improve the reliability and success rate of GLLS for estimating kinetic parameters from noisy data:- incorporation of the volume of distribution (V d ) prior into GLLS and applying the bootstrap Monte Carlo method. Our simulation results show that both methods can improve the parameter estimation reliability at the expense of extra computation time.

关键词： Modelling biomedical systems parameter estimation Monte Carlo simulation

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Improvement of Image Classification with Wavelet and Independent Component Analysis (ICA) based on a Structured Neural Network

Improvement of Image Classification with Wavelet and Indepen...

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International Joint Conference on Neural Networks (IJCNN)

作者： Weibao Zou Yan Li King Chuen Lo Zheru Chi Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Mathematics and Computing University of Southern Queensland QLD Australia Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China

Image classification is a challenging problem in organizing a large image database. However, an effective method for such an objective is still under investigation. This paper presents a method based on wavelet and independent analysis component (ICA) for image classification with adaptive processing of data structures. With wavelet, an image is decomposed into low frequency bands and high frequency bands. An image can be characterized by wavelet coefficients in the form of tree representation. While the histograms of low frequency wavelet bands are effective in characterizing images, the histograms of high frequency wavelet bands are similar for different images and therefore they cannot be directly used as features. We make use of ICA for feature extraction from high frequency bands to improve image classification. Two sets of features are used together to classify images using a structured neural network. In total, 2940 images generated from seven categories are used in experiments. Half of the images are used for training the neural network and the other images used for testing. The classification rate of the training set is 92%, and the classification rate of the test set reaches 89%. The experimental results show the effectiveness of the proposed method based on combining wavelet and ICA for image classification.

关键词： Independent component analysis Image classification Wavelet analysis Neural networks Frequency Histograms Testing Organizing Image databases Image analysis

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EFFICIENT AND AUTOMATIC ABDOMINAL IMAGE REGISTRATION BASED ON ACTIVE CONTOUR

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IFAC Proceedings Volumes 2006年第18期39卷 267-272页

作者： Xiu Ying Wang Cherry Ballangan David Feng Biomedical and Multimedia Information Technology (BMIT) Group School of Information Technologies F09 The University of Sydney NSW 2006 Australia School of Computer Science and Technology Heilongjiang University Harbin 150080 P.R. China . Informatics Department Petra Christian University Indonesia Center for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University

Image registration is critical for making diagnostic decision and essential for image-guided surgery. To improve the quality and accuracy of healthcare, efficient registration is highly demanded. However, because of the non-rigid deformations caused by heartbeat and breath, abdominal image registration remains a challenging task. To address these issues, an automatic and elastic registration for abdominal images is proposed. The algorithm is divided into three steps: efficient non-iterative affine registration; elastic motion field extraction based on active contours; elastic registration based on motion field. The validation of the method on monomodality and multimodality abdominal images has demonstrated that the algorithm is reliable and efficient.

关键词： image registration affine transformations mean-square error computer vision

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Multi-Modal Human Verification Using Face and Speech

Multi-Modal Human Verification Using Face and Speech

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IEEE International Conference on Computer Vision Systems (ICVS)

作者： Changhan Park Joonki Paik Taewoong Choi Soonhyob Kim Youngouk Kim J. Namkung Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Multimedia Signal Processing Laboratory Kwangwoon University Seoul South Korea Precision Machinery Center Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper, we propose a personal verification method using both face and speech to improve the rate of single biometric verification. False acceptance rate (FAR) and false rejection rate (FRR) have been a fundamental bottleneck of real-time personal verification. The proposed multimodal biometric method is to improve both verification rate and reliability in real-time by overcoming technical limitations of single biometric verification methods. The proposed method uses principal component analysis (PCA) for face recognition and hidden markov model (HMM) for speech recognition. It also uses fuzzy logic for the final decision of personal verification. Based on experimental results, the proposed system can reduce FAR down to 0.0001%, which provides that the proposed method overcomes the limitation of single biometric system and provides stable personal verification in real-time.

关键词： Humans Speech Face detection Face recognition Biometrics Principal component analysis Feature extraction Hidden Markov models Image edge detection Laboratories

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Multi-modal human verification using face and speech

Multi-modal human verification using face and speech

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Fourth IEEE International Conference on Computer Vision Systems, ICVS'06

作者： Park, Changhan Choi, Taewoong Kim, Youngouk Kim, Soonhyob Namkung, Jaechan Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-dong Tongjak-Ku Seoul 156-756 Korea Republic of Multimedia Signal Processing Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Intelligent Image Communication Laboratory Department of Computer Engineering Kwangwoon University 447-1 Wolge-dong Nowon-Gu Seoul 139-701 Korea Republic of Precision Machinery Center Korea Electronics Technology Institute 401-402 B/D 193 Yakdae-dong Wonmi-Gu Puchon Kyunggido 420-140 Korea Republic of

ISBN: (纸本)0769525067

关键词： Face recognition

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Chaos-based spread spectrum robust watermarking in DWT domain

Chaos-based spread spectrum robust watermarking in DWT domai...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Lu, Wei Lu, Hong-Tao Chung, Fu-Lai Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200030 China Center for Multimedia Signal Processing Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong

ISBN: (纸本)078039092X

This paper presents a chaos-based robust digital image watermarking scheme in DWT domain. Because chaos is highly sensitive to its initial state, it can be used to permute the original image and make the image's spectrum spread. Entire DWT is applied into the permuted host image. Since the permuted image is a noise-like signal, the high frequency band after DWT is proper for watermark embedding. A binary image watermark is constructed by using chaotic map to embedded in the subband of DWT. Watermark detection is by computing the statistical correlation between the watermarked signal and the original watermark. Experimental results show good performance of the proposed scheme on resisting common watermarking attacks and geometric attacks. ©2005 IEEE.

关键词： Spread spectrum communication

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New parameter estimation approaches for dual-input 11C-acetate liver kinetic model

New parameter estimation approaches for dual-input 11C-aceta...

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作者： Chen, Sirong Feng, Dagan Department of Electronic and Information Engineering Center for Multimedia Signal Processing Hong Kong Polytechnic University Hong Kong Hong Kong Biomedical and Multimedia Information Technology Group School of Information Technologies University of Sydney Australia

ISBN: (纸本)008045108X

11C-acetate uptake in hepatocellular carcinoma (HCC) was reported and the modeling study has been conducted, in which the weighted nonlinear least squares (NLS) algorithm was used to estimate all of the parameters. However, the computational time-complexity of NLS method is high and some estimates are not quite reliable. Due to the hepatic dual blood supply, the current developed fast algorithms could not be used directly. in this paper, two new estimation approaches were presented: Patlak-NLS and Patlak-dual-input-generalized linear least squares. The estimation results demonstrated that these two methods could provide better and practical ways for dual-input 11C-acetate liver kinetic modeling. Copyright © 2005 IFAC.

关键词： Parameter estimation

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Hybrid registration for two-dimensional gel protein images

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3rd Asia-Pacific Bioinformatics Conference, APBC 2005

作者： Wang, Xiuying Feng, David Dagan Group School of Information Technologies University of Sydney Sydney NSW 2006 Australia Center for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong Hong Kong

ISBN: (纸本)1860944779

Image registration technique is fundamental and essential to the accurate and efficient analysis of protein sequence data. But due to the elastic deformations of two-dimensional gel protein eletrophoresis images, their registration still remains a challenge. In this paper, a hybrid 2D gel protein image registration method is proposed. In the first stage of registration, the wavelet-based hierarchical registration which fully exploits the image intensity is used to correct global displacements and affine transformation parameters are achieved. In the second stage, the landmark-based elastic registration is introduced to correct local displacements and enhance registration performance and accuracy. In the proposed method, the hierarchical registration from low resolution to high resolution can accelerate the registration convergence and hence good computational efficiency can be achieved. Though wavelets have been widely used in image processing, its application in the area of gel protein image registration is not well investigated. In this paper, the wavelet-based hierarchical approach is introduced in 2D gel protein image registration. The algorithm makes use of the merits of the existing categories of registration techniques and achieves high performance registration results automatically.

关键词： Image registration

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Chaos-based spread spectrum robust watermarking in DWT domain

Chaos-based spread spectrum robust watermarking in DWT domai...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Wei Lu Hong-Tao Lu Fu-Lai Chung Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China Center for Multimedia Signal Processing and Department of Computing Hong Kong Polytechnic University Hong Kong China

关键词： Chaos Spread spectrum communication Robustness Watermarking Discrete wavelet transforms Chaotic communication Frequency Cryptography Digital images Data security

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