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Medical Imaging 2006: image processing

作者： Sang, Nong Peng, Weixue Li, Heng Zhang, Zhen Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)0819464236

In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is based on the model of generalized cylinders, which are generated by sweeping a two-dimensional cross section along an axis in three-dimensional space. We restrict the cross section to be circular and always perpendicular to the tangent of the axis. Firstly, the vascular centerlines of the X-ray angiography images on both projections are semiautomatically extracted by multiscale vessel tracking using Gabor filters, and the radius of the coronary are also acquired simultaneously. Secondly, the relative geometry of the two projections is determined by the gantry information and 2D matching is realized through the epipolar geometry and the consistency of the vessels. Thirdly, we determine the three-dimensional (3D) coordinates of the identified object points from the image coordinates of the matched points and the calculated imaging system geometry. Finally, we link the consequent cross sections which are processed according to the radius and the direction information to obtain the 3D structure of the artery. The proposed 3D reconstruction method is validated on real data and is shown to perform robustly and accurately in the presence of noise.

关键词： image reconstruction

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TARGET RECOGNITION USING BAYESIAN DATA FUSION METHOD

TARGET RECOGNITION USING BAYESIAN DATA FUSION METHOD

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： YU-QIU SUN JIN-WEN TIAN JIAN LIU School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Co State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute fo State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept.of Elec

Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion is a potential and difficult fusion level. Bayesian fusion method is an important theory in feature level. A new method is presented to fuse infrared images and recognize object in the paper. Firstly,Bayesian principles, fusion mode and recognition decision function are described. Then, aiming at the features of mid-wave infrared image and long-wave infrared image, we use Bayesian probability to fuse them. Last, recognize target and background obtained with training and test pattern vectors. The experiment results show stability and feasibility of the fusion recognition using Bayesian decision theory in infrared image.

关键词： Bayesian decision data fusion target recognition infrared images

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An Adaptive Fractional Pixel Search Algorithm

An Adaptive Fractional Pixel Search Algorithm

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International Conference on Intelligent Sensing and Information processing (ICISIP)

作者： Liquan Shen Zhaoyang Zhang Zhi Liu Wenjun Zhang Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai University Shanghai China Institute of Image Communication& Information Processing Shanghai Jiaotong University China

In this paper, we propose an adaptive fractional pixel search algorithm for reduction computation its load. Based on that SAD (sum of absolute difference) error surface is unimodal within the range of plusmn1 pixel, a novel fractional pixel search bypass strategy is first proposed; Then, a strategy of fractional pixel search early termination based on all-zero block detection is proposed. Finally, an adaptive fractional pixel search algorithm adopting above strategies and improved CBFPS (center biased fractional pixel search) algorithm is proposed. Compared with the fractional pixel full search algorithm and JVT-F017 that adopts CBFPS, simulation results show that the proposed algorithm can reduce 76.60% and 68.22% fractional pixel search points respectively while it still maintains similar coding efficiency.

关键词： Motion estimation Vectors Video coding Testing Paramagnetic resonance Pixel image communication Information processing Computer displays Redundancy

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A Super Performance Bandgap Voltage Reference with Adjustable Output for DC-DC Converter

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The Journal of China Universities of Posts and Telecommunications 2006年第1期13卷 75-78页

作者： YU Hua ZOU Xue-cheng CHEN Chao-yang Department of Electronics Science and Technology Huazhong University of Science and Technology Wuhan 430074 P.R. China State Key Laboratory for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan 430074 P.R. China

This paper presents a super performance bandgap voltage reference for DC-DC converter with adjustable output. it generates a wide range of voltage reference ranging from sub- 1V to 1,221 7 V and has a low temperature coefficient of 2.3 × 10 ^5/K over the temperature variation using the current feedback and resistive subdivision. In addition, the power supply rejection ration of the proposed bandgap voltage reference is 78 dB. When supply voltage varies from 2.5 V to 6 V, output VREF is 1,221 685±0.055 mV.

关键词： bandgap voltage reference adjustable output DC-DC converter temperature coefficient PSRR

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Combination of PCA and LORETA for sources analysis of ERP data: An emotional processing study

Combination of PCA and LORETA for sources analysis of ERP da...

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Medical Imaging 2006: Physiology, Function, and Structure from Medical images

作者： Hu, Jin Tian, Jie Yang, Lei Pan, Xiaohong Liu, Jiangang Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Science P.O.Box 2728 Beijing 100080 China Graduate University Chinese Academy of Science Beijing 100080 China State's Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University 100871 China

ISBN: (纸本)0819461865

The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. An analysis of two steps was applied to the ERP data. First, principal component analysis was performed to obtain significant ERP components. Then LORETA was applied to each component to localize their brain sources. The first six principal components were extracted, each of which showed different spatiotemporal patterns of neuronal activity. The results agree with other emotional study by fMRI or PET. The combination of PCA and LORETA can be used to analyze spatiotemporal patterns of ERP data in emotional processing.

关键词： Principal component analysis

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Rapid Multi-modality preRegistration based on SIFT descriptor

Rapid Multi-modality preRegistration based on SIFT descripto...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jian Chen Jie Tian Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences China

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration

关键词： Biomedical imaging Lighting Robustness image registration Computer vision image analysis Histograms Cities and towns USA Councils Computational complexity

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Multi-modal Medical image Registration Based on Adaptive Combination of Intensity and Gradient Field Mutual Information

Multi-modal Medical Image Registration Based on Adaptive Com...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jiangang Liu Jie Tian Yakang Dai Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences China

Mutual information (MI) is an effective criterion for multi-modal image registration. However the traditional MI function only includes intensity information of images and lacks sufficient spatial information to accurately measure the degree of alignment of two images, and besides, it is apt to be influenced by intensity interpolation, therefore presents many local maxima which frequently lead to misregistration. Our paper proposes a criterion of adaptive combination of intensity and gradient field mutual information (ACMI). Unlike the intensity MI computed from two original images, the gradient field MI of two images is calculated from their gradient code maps (GCM) constructed by coding the gradient field information of corresponding original image. Because of their complementary properties, these two MI functions are combined to form ACMI by a nonlinear weight function which can be adaptively regulated according to their performances and make the better dominant in the combination. Experimental results demonstrate that the ACMI outperforms the traditional MI and furthermore the former is much less sensitive than the latter to the reduction of resolution or overlapped region of images

关键词： Biomedical imaging image registration Mutual information image resolution Entropy Interpolation Biomedical image processing Cities and towns USA Councils image coding

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Speckle reduction of polarimetric SAR images based on neural ICA

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13th International Conference on Neural Information processing, ICONIP 2006

作者： Jian, Ji Zheng, Tian Department of Computer Science and Technology Northwestern Polytechnical University Xi'an 710072 China Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3540464816

The polarimetric synthetic aperture radar (PSAR) images are modeled by a mixture model that results from the product of two independent models, one characterizes the target response and the other characterizes the speckle phenomenon. For the scene interpretation, it is desirable to separate between the target response and the speckle. For this purpose, we proposed a new speckle reduction approach using independent component analysis (ICA) based on statistical formulation of PSAR image. In addition, we apply four ICA algorithms on real PSAR images and compare their performances. The comparison reveals characteristic differences between the studied neural ICA algorithms, complementing the results obtained earlier. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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Robust ICA neural network and application on Synthetic Aperture Radar (SAR) image analysis

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13th International Conference on Neural Information processing, ICONIP 2006

ISBN: (纸本)3540464816

Independent component analysis (ICA) has shown success in the separation of sources in lots of applications. However, in synthenic aperture radar (SAR) images the noise is multiplicative, so the applicability of ICA is seriously reduced. This paper proposes a new robust independent component analysis neural network (RICANN) that improves the robustness of ICA by adding outlier rejection rule. Its application in synthetic aperture radar (SAR) is discussed. The results show the potential usage in SAR image processing problems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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Neighborhood aided implicit active contours

Neighborhood aided implicit active contours

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2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006

作者： Liu, Huafeng Chen, Yunmei Chen, Wufan Shi, Pengcheng State Key Laboratory of Modern Optical Instrumentation Zhejiang University Hangzhou China Department of Electrical and Electronic Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong Hong Kong Department of Mathematics University of Florida Gainesville FL United States Key Laboratory of Medical Image Processing Southern Medical University Guangzhou China

ISBN: (纸本)0769525970

We have developed a geometric deformable model that employs neighborhood influence to achieve robust segmentation for noisy and broken edges. The fundamental power of this strategy rests with the explicitly combination of regional inter-point constraints, image forces, and a priori boundary information for each geometric contour point within its adaptively determined local influence domain. This formulation thus naturally unifies the essences of the geometric and parametric snakes through automatic local scale selection, and exhibits their respective fundamental strengths of allowing stable boundary detection when the edge information is weak and possibly discontinuous, while maintaining the abilities to handle topological changes during front evolution. In particular, this paper presents an implementation of the method through local integration of the level set function and the image/prior-driven evolution forces, where the resulting partial differential equation is solved numerically using standard finite difference method. Experimental results on synthetic and real images demonstrate its superior performance. © 2006 IEEE.

关键词： Edge detection

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