检索结果-内蒙古大学图书馆

IEEE International Conference on image processing

作者： Melih S. Aslan Eslam Mostafa Hossam Abdelmunim Ahmed Shalaby Aly A. Farag Ben Arnold Computer Vision and Image Processing Lab. University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc. Columbia KY USA

We propose a new shape-based segmentation approach using the statistical shape prior and level sets method. The segmentation depends on the image information and shape prior. Training shapes are grouped to form a probabilistic model. The shape model is embedded into the image domain taking in consideration the evolution of a contour represented by a level set function. The evolution of the front gathers information from the image intensities and shape prior. The segmentation approach is applied in segmenting the vertebral bodies in CT images. Our results shows that the technique is accurate and robust compared with the other alternative in the literature.

关键词： Shape image segmentation Level set Computed tomography Accuracy Probabilistic logic

来源：评论

学校读者我要写书评

暂无评论

Variational approach for segmentation of lung nodules

Variational approach for segmentation of lung nodules

引用

IEEE International Conference on image processing

作者： Amal A. Farag Hossam Abdelmunim James Graham Aly A. Farag Salwa Elshazly Sabry El-Mogy Mohamed El-Mogy Robert Falk Sahar Al-Jafary Hani Mahdi Rebecca Milam Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA Computer & Systems Engineering Department Faculty of Engineering Ain Shams University Cairo Egypt School of Medicine Mansoura University Egypt FJewish Hospital and 3DR Louisville KY USA Department of Radiology University of Louisville USA

Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets. The outline of the nodule region is further improved using the curvature characteristics of the segmentation boundary. We illustrate the effectiveness of this method for automatic segmentation of the Juxta-pleural nodules.

关键词： Lungs image segmentation Computed tomography Level set Shape Conferences Databases

来源：评论

学校读者我要写书评

暂无评论

Simulation of realistic infrared texture of grassland

引用

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2011年第12 SUPPL.期32卷 103-108页

作者： Liu, Qian Zhu, Feng Hao, Yingming Shenyang Institute of Automation Chinese Acad. of Sci. Shenyang 110016 China Graduate School of the Chinese Acad. of Sci. Beijing 110080 China Key Laboratory of Opto-Electronics Information Processing Chinese Acad. of Sci. Shenyang 110016 China Key Lab. of Image Understanding and Computer Vision Liaoning Shenyang 110016 China

A new method is introduced to simulate realistic infrared texture of grassland. First, the radiative temperature of grassland is solved by integrating material composition, environmental and meteorological factors. As the spectroscopic properties of grass and soil vary greatly, the infrared radiation characteristics are computed respectively. Next, the texture structure of grassland is modeled based on the analysis of spatial distribution of natural grassland. Finally, the infrared radiance of grass and soil are mapped to image space and a realistic grassland texture is generated. Experiment results show that similar visual features exhibit between simulated textures and actual grassland textures, which justifies the effectiveness of the proposed method.

关键词： Infrared radiation

来源：评论

学校读者我要写书评

暂无评论

labelling color images by modelling the colors density using a linear combination of Gaussians and EM algorithm

Labelling color images by modelling the colors density using...

引用

IEEE International Conference on image processing

作者： Asem M. Ali Amal A. Farag Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY

Parametric density estimation is widely used to solve many image processing problems. We examined the parametric estimation using linear combination of 1D Gaussians in many works. In this work, we extend our model to estimate density of the colors in color images. We approximate the marginal density of each class in the empirical probability density function by a 3D Gaussian distribution. Then, the deviation between the estimated and the empirical densities is modelled using a linear combination of 3D Gaussians with positive and negative components. We estimate the parameters of this model using our modified EM algorithm. The proposed framework demonstrates very promising experimental results of color images labelling and can be integrated with many other frameworks.

关键词： labeling Color Gaussian processes Function approximation Probability density function image processing Gaussian distribution Parameter estimation image segmentation Gaussian approximation

来源：评论

学校读者我要写书评

暂无评论

A variational framework for 3D colonic polyp visualization in virtual colonoscopy

A variational framework for 3D colonic polyp visualization i...

引用

IEEE International Conference on image processing

作者： Dongqing Chen Aly A. Farag Robert L. Falk Gerald W. Dryden Computer Vision & Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Jewish Hospital Louisville KY USA Division of Gastroenterology/Hepatology University of Louisville Louisville KY USA

Colorectal cancer includes cancer of the colon, rectum, anus and appendix. Since it is largely preventable, it is extremely important to detect and treat the colorectal cancer in the earliest stage. Virtual colonoscopy is an emerging screening technique for colon cancer. One component of virtual colonoscopy, image pre-processing, is important for colonic polyp detection/ diagnosis, feature extraction and classification. This paper introduces a general variational approach based framework for a computer aided diagnosis system for colorectal cancer. It includes techniques for 3D colon segmentation, 3D colon object reconstruction by iso-surface generation, and 3D centerline extraction. The proposed framework has been validated on 22 real CT colonography datasets.

关键词： Colonic polyps Visualization Virtual colonoscopy Cancer Colon Colonography image segmentation Optical computing Computed tomography image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Accurate and fast 3D colon segmentation in CT colonography

Accurate and fast 3D colon segmentation in CT colonography

引用

IEEE International Symposium on Biomedical Imaging

作者： Dongqing Chen Rachid Fahmi Aly A. Farag Robert L. Falk Gerald W. Dryden Computer Vision & Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Department of Medical Imaging Jewish Hospital and Saint Marys Healthcare Louisville KY USA Division of Gastroenterology/Hepatology Department of Medicine University of Louisville Louisville KY USA

ISBN: (纸本)9781424439317

This paper introduces an adaptive level set method for 3D segmentation of colon tissue in CT colonography filled with air and opacified fluid. First, most of the opacified liquid is removed by a threshold value. The closed contours are propagated toward the desired 3D region boundaries through the iterative evolution of the adaptive level sets function. The proposed method has been tested on 22 real CT colonography datasets with various pathologies, and the segmentation accuracy has achieved 98.40%.

关键词： Colonography Colon Virtual colonoscopy Cancer image segmentation Colonic polyps Level set Deformable models Computed tomography Visualization

来源：评论

学校读者我要写书评

暂无评论

A novel framework for N-D multimodal image segmentation using graph cuts

A novel framework for N-D multimodal image segmentation usin...

引用

IEEE International Conference on image processing

作者： Asem M. Ali Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

This work proposes a new MAP-based segmentation framework of multimodal images. In this work a joint MGRF model is used to describe the image. The main focus here is a more accurate model identification. For a known number of classes in the given image, the empirical distributions of this image signals are precisely approximated by a LCG distributions with positive and negative components. Gibbs potential, which is used to identify the spatial interaction between the neighboring pixels, is analytically estimated. Finally, an energy function using the previous models is formulated and is globally minimized using graph cuts. Experiments show that the developed technique gives promising accurate results compared to other known algorithms.

关键词： image segmentation Pixel Joining processes labeling image processing Gray-scale Robustness Object segmentation computer vision laboratories

来源：评论

学校读者我要写书评

暂无评论

Density estimation using a new AIC-type criterion and the EM algorithm for a linear combination of Gaussians

Density estimation using a new AIC-type criterion and the EM...

引用

IEEE International Conference on image processing

作者： Asem M. Ali Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP Lab) University of Louisville Louisville KY USA

We propose a new approach that approximates an empirical probability density function of scalar data with a linear combination of Gaussians (LCG). The proposed algorithm approximates the marginal density of each class using a Gaussian distribution. Number of the classes and their distributions parameters are estimated using a new Akaike Information Criterion (AlC)-type criterion and the Expectation- Maximization (EM) approach. Each class does not follow perfect Gaussian distribution so we refine the initial LCG model using a modified EM algorithm. The modified EM algorithm approximates the marginal density of each class using a LCG with positive and negative components. Experiments in segmenting multimodal medical images show that the developed technique gives promising accurate results.

关键词： Gaussian processes Function approximation Probability density function Gaussian approximation Gaussian distribution Parameter estimation image processing Clustering algorithms image segmentation Probability distribution

来源：评论

学校读者我要写书评

暂无评论

A new symmetric shape from shading algorithm with an application to 3-D face reconstruction

A new symmetric shape from shading algorithm with an applica...

引用

IEEE International Conference on image processing

作者： Abdelrehim Ahmed Aly Farag Thomas Starr Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

This paper presents a new symmetric shape from shading (SFS) algorithm where the self-ratio image irradiance equation proposed by Zhao and Chellappa is formulated as a partial differential equation (PDE) with a Dirichlet boundary condition. This PDE is solved using the Lax-Friedrichs sweeping method. The potential of the proposed symmetric SFS algorithm is demonstrated by several experiments on synthetic and real data. As an application, the proposed algorithm is used for 3-D face reconstruction.

关键词： Shape Partial differential equations Iterative algorithms Rough surfaces Surface roughness Face image reconstruction Differential equations Brightness Nonlinear equations

来源：评论

学校读者我要写书评

暂无评论

Elastic Registration of the Corpus Callosum

Elastic Registration of the Corpus Callosum

引用

IEEE International Conference on image processing

作者： Hossam E. Abd El Munim Aly A. Farag Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY 40292. Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

Geometric analysis of postmortem normal and autistic human subjects reveal distinctions in deformations in the corpus callosum (CC) that may be used for image analysis-based studies of autism. Preliminary studies showed that the CC of autistic patients is quite distinct from normal controls. We use an implicit vector representation of CC to carry out the registration process which measures the differences between different CC's. This paper introduces a new method for the 2D shape registration problem by matching vector distance functions. A variational frame work is proposed for the global and local registration of CC's. A gradient descent optimization is used which can efficiently handle both the rigid and the non-rigid operations together. The registration of real CC extracted from postmortem data sets demonstrates the potential of the proposed approach.

关键词： Shape measurement Autism computer vision Magnetic resonance imaging image analysis image processing laboratories Humans Area measurement computer graphics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：