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3D reconstruction of the coronary tree from two X-ray angiographic views

3D reconstruction of the coronary tree from two X-ray angiog...

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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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Dim Small Targets Detection Based on Dualband Infrared image Fusion

Dim Small Targets Detection Based on Dualband Infrared Image...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recongnition and Artificial Intelliegence Huazhong University of Science and Technology Wuhan China School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast thresholding. The experimental results show that the method using fractal dimension to fuse dualband infrared images, and then detect targets is superior to use mid-wave or long -wave infrared images detect targets alone.

关键词： Object detection Dual band Infrared imaging Infrared detectors image fusion Fuses Fractals Concrete Shape Wavelet domain

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Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology

Dualband Infrared Images Target Detection Algorithm Based on...

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2006 8th International Conference on Signal processing

作者： Yuqiu Sun Jinwen Tian Jian Liu School of Information and Mathematics Yangtze University State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology

According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features such as local maximum gray level and average gradient strength of every image are extracted at each level of morphology *** dualband infrared images based on fusion rule put forward in the paper,and then reconstruct original image and detect target using contrast threshold *** experiment results show that dualband infrared images target detection algorithm based on multiscale morphology algorithm is better than use mid-wave or long-wave infrared images detect targets alone.

关键词： image Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology Target

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Speckle reduction of polarimetric SAR images based on neural ICA

引用

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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A Combining Method for Tumors Detection from Near-infrared Breast Imaging

A Combining Method for Tumors Detection from Near-infrared B...

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

作者： Zhicheng Wang Jian Liu Jinwen Tian Zeping Xie State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. & Tech. Wuhan 430074 China Key Lab. for Image Process. & Intelligent Control State Educ. Comm. School of Life Science & Technology Huazhong University of Science and Technology Wuhan China

This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnostic approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer

关键词： Breast tumors Displays Pathology Blood vessels Biomedical imaging Pixel Feature extraction Anisotropic magnetoresistance Smoothing methods Breast cancer

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Contrast-modulated Nonlinear Diffusion for X-ray Angiogram images

Contrast-modulated Nonlinear Diffusion for X-ray Angiogram I...

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

作者： Baopu Li Nong Sang Zhiguo Cao Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China

In this paper, we present a new method for X-ray angiogram images enhancement using a contrast-modulated nonlinear diffusion. The original nonlinear diffusion is gradient driven, which leads into much dependence on the accurate estimation of the edge. However, it is very difficult to get the accurate estimation of edges for X-ray angiogram images, which are characterized with complex background. So it is necessary to do some improvements to this model. By designing a new concept of contrast space according to the characteristics of these images, we change the original nonlinear diffusion into contrast-modulated nonlinear diffusion. Compared with the traditional method, this new approach is proved to have a better performance of enhancement

关键词： X-ray imaging Anisotropic magnetoresistance image processing image analysis control engineering education intelligent control image enhancement Biomedical imaging Medical diagnostic imaging Chemicals

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A support value transform-based multi focus image fusion method

A support value transform-based multi focus image fusion met...

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International Conference on Signal processing Proceedings (ICSP)

作者： Sheng Zheng Jian Liu Guangxi Zhu Jinwen Tian Electronic & Information Engineering Department Huazhong University of Science and Technology Wuhan China College of Electrical Engineering & Information Technology China Three Gorges University Yichang China State Edu Commission Key Laboratory for Image Processing & Intelligent Control HUST Wuhan China Chinese Key laboratory of optic & electronics HUST Wuhan China

The image fusion is an important approach to produce a single complete image which preserves all relevant information from different sensors. In this paper, we proposed a support value transform-based multi focus image fusion method, where the fused saliency features are represented by support values. Based on the mapped least squares support vector machine, the support value transform is developed as a multi-scale analysis tool. The fusing results on the multi focus images demonstrate that the proposed image fusion method is effective and efficient

关键词： Focusing image fusion Support vector machines Discrete wavelet transforms Optical sensors image sensors Sensor fusion Support vector machine classification image processing Least squares methods

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3D TRUS image Segmentation in Prostate Brachytherapy

3D TRUS Image Segmentation in Prostate Brachytherapy

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

作者： Mingyue Ding L. Gardi Zhouping Wei A. Fenster Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Imaging Research Laboratories Robarts Research Institute London ONT Canada

Brachytherapy is a minimally invasive interventional surgery used to treat prostate cancer. It is composed of three steps: dose pre-planning, implantation of radioactive seeds, and dose post-planning. In these procedures, it is crucial to determine the positions of needles and seeds, measure the volume of the prostate gland. Three-dimensional transrectal ultrasound (TRUS) imaging has been demonstrated to be a useful technique to perform such tasks. Compared to CT, MRI or X-ray imaging, US image suffers from low contrast, image speckle and shadows, making it challenging for segmentation of needles, the prostates and seeds in the 3D TRUS images. In this paper, we reviewed 3D TRUS image segmentation methods used in prostate brachytherapy including the segmentations of the needles, the prostate, as well as the seeds. Furthermore, some experimental results with agar phantom, turkey and chicken phantom, as well as the patient data are reported

关键词： image segmentation Brachytherapy Needles Minimally invasive surgery Ultrasonic imaging Imaging phantoms Oncological surgery Prostate cancer Position measurement Volume measurement

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ROAD CENTRAL CONTOUR EXTRACTION FROM HIGH RESOLUTION SATELLITE image USING TENSOR VOTING FRAMEWORK

ROAD CENTRAL CONTOUR EXTRACTION FROM HIGH RESOLUTION SATELLI...

引用

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

作者： SHENG ZHENG JIAN LIU WEN-ZHONG SHI GUANG-XI ZHU Electronic & Information Engineering Dept. Huazhong University of Science and Technology Wuhan 430 State Education Commission Key Laboratory for Image Processing and Intelligent Control Inst.for Pat Advanced Research Center for Spatial Information Technology Department of Land Surveying and Geo-In Chinese Key lab of optic & electronics Huazhong University of Science and Technology Wuhan 430074

In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed merely to classify the image into two groups of categories: a road group and a non-road group. The identified road group images are the discrete and irregularly distributed sampled points, and they are an uncompleted data set for the road. Secondly, the road contour was extracted from the road group images using the tensor voting framework, since the tensor voting technique is superior to the traditional methods in extracting the geometrical structure from the uncompleted data set. The experimental results on the high resolution satellite image demonstrate that the proposed approach worked well with images comprised by both rural and urban area features.

关键词： Tensor voting framework Road central line extraction High-resolution satellite image

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