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检索条件"机构=Key Laboratory of Education Ministry for Image Processing and Intelligent Control"

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Geometric Active Contour Model and its Application to Carotid Plaque Detection

Geometric Active Contour Model and its Application to Caroti...

引用

International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Jieyu Cheng Mingyue Ding Xuming Zhang Life School of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

This paper gives an overview of three different geometric active contour models with the focus on the application to carotid plaque detection from cross-sectional ultrasound images of the carotid artery. On one hand, basic principles of these geometric active contour models are presented. On the other hand, performance of these models are tested on 16 images and compared with the manual delineations.

关键词： Active contours image segmentation Computational modeling Manuals Level set Ultrasonic imaging Solid modeling

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Prostate Surgery Path Planning Based on Simplified Delay-PCNN

Prostate Surgery Path Planning Based on Simplified Delay-PCN...

引用

International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： He Li Xuming Zhang Wenguang Hou Mingyue Ding Life School of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

This paper presents an algorithm to find the shortest path in 3D(three-dimensional) prostate surgery planning. Using a simplified delay pulse coupled neural network(S-DPCNN) model, a shortest path can be drawn automatically from the target position to the puncture point. Compared to the traditional pulse coupled neural network(PCNN), S-DPCNN needs much fewer neurons and therefore decreases complexity of computation. Experiments on computer simulations show the validity of this method.

关键词： Neurons Path planning Solid modeling Joining processes Biological neural networks Three dimensional displays Surgery

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A Three-Dimensional Transrectal Ultrasound Imaging System

A Three-Dimensional Transrectal Ultrasound Imaging System

引用

International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Yimin Chen Jian Qi Xuming Zhang Mingyue Ding School of Life Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

A three dimensional transrectal ultrasound imaging system has been developed. The proposed system is aimed at monitoring for the prostate and providing three-dimensional ultrasound image for prostate biopsy and therapy. The device contains mechanical device and control circuit for the rotation of the probe. In addition, a two dimensional ultrasound machine for 2D ultrasound imaging is used and the software system for the reconstruction of three-dimensional ultrasound image based on PC is developed. Experiments are performed in phantom to validate our prototype. The 3D scan of the agar phantom produces minimal geometric distortion. In the future, our system will be tested on patients.

关键词： Ultrasonic imaging Phantoms Three dimensional displays Transducers image reconstruction Biopsy

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Spectral clustering based unsupervised change detection in SAR images

Spectral clustering based unsupervised change detection in S...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiangrong Zhang Zemin Li Biao Hou Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

An unsupervised change detection method based on spectral clustering and difference image methods for multitemporal single-channel single-polarization synthetic aperture radar (SAR) images is proposed. The difference image is generated by integrating the typical difference image method with Non-Local Filter, which exploits both the spatial neighborhood information and gray similarity information, and can well reduce the speckle noises of SAR images. The spectral clustering algorithm is employed to cluster the difference image into two clusters and get the change map. Compared with traditional clustering algorithms, such as A-means, SC can recognize the clusters of unusual shapes and obtain the globally optimal solutions. Experimental results confirm the effectiveness of the proposed techniques.

关键词： Clustering algorithms Remote sensing Principal component analysis Change detection algorithms Synthetic aperture radar Sensors Noise

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image Denoising with Non-Local Means in the Shearlet Domain

Image Denoising with Non-Local Means in the Shearlet Domain

引用

International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Xiaohua Zhang Qiang Zhang L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, a novel method for image denoising is proposed which adopts multiscale geometry tool. Firstly the image is decomposed by discrete shearlet transform. The shearlet coefficients of each direction approach the generalized Gaussian distribution. We use the principal component analysis (PCA) for every similarity window of shearlet coefficients. Then we use Generalized Gaussian model of non-local means method to handle the shearlet coefficients. Finally, we reconstruct image with the new shearlet coefficients to obtain the result. Numerical results show that our algorithm competes favorably with nonlocal means algorithms in the case of high noise.

关键词： image denoising Transforms Pixel Principal component analysis Algorithm design and analysis Noise reduction Noise

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SAR image Despeckling via Spatially Constrained Multiscale Products

SAR Image Despeckling via Spatially Constrained Multiscale P...

引用

2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

作者： X. L. Tian L. C. Jiao X. H. Zhang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

This paper presents a wavelet-based multiscale products scheme for synthetic aperture radar (SAR) image despeckling. A compactly supported quadratic spline function that approximates the first derivative of Gaussian is employed in the scheme to decompose log-transformed SAR images. The multiplied results of the decomposed coefficients of adjacent scales consist of multiscale products. The multiscale products can sharp the important structures while weakening noise. A spatially selective neighborhood technique by iteratively selecting neighborhood system in the multiscale products is introduced in searching the important structure information. The influence of the spatial information is imposed on the multiscale products, instead of on the wavelet coefficients, which improves the capability of identifying important features. Experiments show that the proposed scheme is better in SAR image despeckling and preserving edges and detail information than other waveletbased multiscale products methods.

关键词： Despeckling synthetic aperture radar multiscale products wavelet transform neighborhood system

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Partial Differential Equation Model Method Based on image Feature for Denoising

Partial Differential Equation Model Method Based on Image Fe...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Xiaohua Zhang Ran Wang L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts.

关键词： Mathematical model TV image edge detection Noise reduction Noise Noise measurement Numerical models

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An analysis of the eigenvalues method for polarimetric SAR image classification

An analysis of the eigenvalues method for polarimetric SAR i...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S. P. Gou Xin. Qiao L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, we focus on the distribution of eigenvalues, and based on Gaussian assumption, then we do an analysis of the eigenvalues potential for POL-SAR classification. Generally, we use Gaussian mixture model to describe the distribution of the eigenvalue and Bayesian classifier to achieve the POL-SAR pixel classification. The method is tested with the NASA/JPL AIRSAR data.

关键词： Decision support systems

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Ultrasound carotid artery Intima-Media Thickness (IMT) segmentation review

Ultrasound carotid artery Intima-Media Thickness (IMT) segme...

引用

2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Yang, Xin Jin, Jiaoying Yuchi, Ming Ding, Mingyue Huazhong University of Science and Technology HUST Wuhan Hubei 430074 China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology HUST Wuhan Hubei 430074 China

ISBN: (纸本)9780769546230

Stroke and heart attack, which could be led by a kind of cerebrovascular and cardiovascular disease named asatherosclerosis, would seriously cause human morbidity and mortality. And the carotid artery of intima-media thickness (IMT) is a key indicator to the disease. With the development of computer assisted diagnosis (CAD) technology, Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology especially for the measurement of IMT. This review is an attempt to discuss the clinical relevance of measurements in clinical practice at first, and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images. Secondly, the paper is presentation of common used methods for the IMT segmentation and measurement. An overview of summary and future perspectives is given in conlusion finally. © 2011 IEEE.

关键词： Diseases

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Research on Fuzzy Enhancement in the Diagnosis of Liver Tumor from B-mode Ultrasound images

Research on Fuzzy Enhancement in the Diagnosis of Liver Tumo...

引用

International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Wu Qiu Rui Wang Feng Xiao Mingyue Ding School of Life Science and Technololgy Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

Fuzzy enhancement is applied in computer aided diagnosis of liver cancer from B mode ultrasound images as a pre-processing procedure in this paper. It was evaluated with three classifiers including K means, back propagation neural network and support vector machine using 25 features from first order statistic (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), Grey level dependant matrix (GLDM) and LAWS. In the analysis of 166 normal liver tissue, 30 hemangioma and 60 malignant tumor, our method improved the classification accuracy of three classifiers (K means, BP neural network and support machine vector) in distinguishing liver cancer, hemangioma and normal liver cancer from B mode ultrasound images. It is proved that fuzzy enhancement as an efficient preprocessing procedure could be used in the computer aided diagnosis system of liver cancer.

关键词： Liver Cancer Ultrasonic imaging Feature extraction Artificial neural networks Accuracy Support vector machines

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