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International Conference on Pattern Recognition

作者： S. Zambanini G. Langs R. Sablatnig P. Donath H. Maier Pattern Recognition and Image Processing Group University of Technology Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Division of Special and Environmental Dermatologyy Medical University of Vienna Austria

This paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. The algorithm computes the spatial resolution of an image. Hemangioma segmentation is accomplished by a single-layer perceptron classification by means of pixel color features. The algorithm was evaluated on a set of 120 images. It achieves satisfactory results on images with clearly visible, saturated hemangiomas

关键词： image segmentation Neoplasms Pattern recognition Spatial resolution Lesions Area measurement Pixel image processing computer graphics Biomedical imaging

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Validating linear elastic and linear viscoelastic models of lamb liver tissue using cone-beam CT

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International Congress Series 2005年 1281卷 473-478页

作者： Shi, Hongjian Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

The purpose of this paper is to validate simple linear elastic model and linear viscoelastic models for lamb liver tissue deformation using high resolution cone-beam CT images. The resolution of the scanned images is 5 to 25 times higher than typical CT scans. The tissue deformation details in the contact region between the tissue and the indentor can be detected and rendered for smaller force loads. For these loads, it is difficult to accurately predict the volume and surface changes using typical low resolution CT scans. Surgical simulations rely on the accurate representation of the mechanical response of the soft tissues which are subject to surgical manipulations. If the simulation results using a model are quite different from reality, it can be concluded that such model is not applicable to the modelling of the targeted tissue. From simulation results we compare the deformed tissue with that obtained from experiments to verify the applicability of the model to soft tissue deformation. For our validation, fresh ex vivo lamb liver is chosen to validate the linear elastic model and the linear viscoelastic model. © 2005.

关键词： Cone-beam CT Finite element modeling Tissue deformation

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Non-rigid registration techniques for automatic follow-up of lung nodules

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International Congress Series 2005年 1281卷 1115-1120页

作者： El-Baz, Ayman Yuksel, Seniha E. Elshazly, Salwa Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

Our long-term research goal is to develop an automatic approach for early detection of lung nodules that may lead to lung cancer. This paper focuses on the monitoring of the progress (growth or shrinking) of lung nodules in successive chest low dose CT (LDCT) scans of a person using non-rigid registration. The overall nodule detection approach consists of four main steps: (1) extraction of lung region by modeling the gray level distribution of LDCT slices using a linear combination of Gaussians, (2) classifying the lung region into homogenous tissues, arteries, veins and lung nodules, (3) applying rigid registration using a combination of segmentation information and mutual information as a similarity measure, and (4) compensating for the effects of heartbeats and respiration using non-rigid registration. Our earlier work addressed a number of steps in this protocol;this paper focuses on the registration step. We show that proper registration could lead to precise identification of the progress of the lung nodules. © 2005.

关键词： Lung nodules Motion compensation Mutual information Registration Segmentation

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Virtual forces for camera planning in smart vision systems

Virtual forces for camera planning in smart vision systems

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7th IEEE Workshop on Applications of computer vision, WACV 2005

作者： Farag, Aly A. Abdel-Hakim, Alaa E. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0769522718

In this paper, we present a novel and robust approach for camera planning in smart vision systems. The proposed approach uses virtual forces to adjust the camera parameters (pan, tilt, translation ... etc.) toward the most proper values with respect to the application. It employs the physical spring model to direct the motion of the camera toward its target. Our approach is a general framework and any vision system can be easily modeled to use it. This approach has several advantages over previous work in camera planning. It is portable, expandable, robust, and flexible. We present a case study of a two degree-of-freedom stereo vision system to test our approach. The results show the efficiency of our approach even with poor system initialization and its robustness against possible weakness in the auxiliary algorithms used.

关键词： Stereo vision

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Brain MR image segmentation using tabu search and hidden markov random field model

Brain MR image segmentation using tabu search and hidden mar...

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2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

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Automatic detection of renal rejection after kidney transplantation

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International Congress Series 2005年 1281卷 773-778页

作者： Yuksel, S.E. El-Baz, A. Farag, A.A. Abo El-Ghar, M.E. Eldiasty, T.A. Ghoneim, M.A. Computer Vision and Image Processing Lab University of Louisville Louisville KY 40292 United States Mansoura University Urology and Nephrology Center Mansoura Egypt

Acute rejection is the most important reason of graft failure after kidney transplantation, and early detection is crucial to survive the kidney function. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is an imaging modality where a contrast agent (such as Gd-DTPA) is introduced into the kidney and rapid and repeated images are taken, which allows both the anatomic and functional information of the kidney to be monitored. Using these images, this paper introduces an accurate method for the segmentation of the kidney from the surrounding structures by introducing a shape model of the kidney into the external energy component of the deformable models. Secondly, registration algorithms are employed to account for the motion of the kidney due to patient breathing and finally, the perfusion curves obtained from the cortex that show the transportation of the contrast agent into the tissue are given for future classification of normal and acute rejection transplants. Applications of the proposed algorithms yield promising results. © 2005.

关键词： Contrast agents Deformable models Dynamic MRI Gd-DTPA Kidney transplantation Mutual information Renal rejection

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A volumetric 3D model of the human jaw

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International Congress Series 2005年 1281卷 1244-1249页

作者： Hassan, Hossam El-Baz, Ayman Farag, Aly A. Farman, Allan G. Tasman, D. Miller, William M. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States Dental School University of Louisville Louisville KY United States

The purpose of this paper is to introduce a detailed approach for constructing a complete model of the human jaw. Our previous work developed an accurate model of the human jaw surface. Unfortunately this surface is not enough for the analysis purpose which requires a detailed model of the teeth and their roots. A database of volumetric 3D models of teeth is constructed from the CT scans. The crown the tooth coming from the shape modeling algorithm provided in our previous work is matched with one of the database teeth. A registration technique is used to deform the matched tooth with our previous derived surface model. Combining this information with the jaw details and X-ray information of the roots, we can now derive a complete volumetric 3D model of the human jaw. This model is suitable for the analysis process which will include finite element work to analyze the stress and strain for different simulations. The simulations processes will include, among others, tooth-implanting and alignment. © 2005.

关键词： Human jaw Registration Segmentation

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2D and 3D shape based segmentation using deformable models

2D and 3D shape based segmentation using deformable models

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8th International Conference on Medical image Computing and computer-Assisted Intervention - MICCAI 2005

作者： El-Baz, Ayman Yuksel, Seniha E. Shi, Hongjian Farag, Aly A. El-Ghar, Mohamed A. Eldiasty, Tarek Ghoneim, Mohamed A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 Mansoura University Urology and Nephrology Center Mansoura Egypt

ISBN: (纸本)3540293264

A novel shape based segmentation approach is proposed by modifying the external energy component of a deformable model. The proposed external energy component depends not only on the gray level of the images but also on the shape information which is obtained from the signed distance maps of objects in a given data set. The gray level distribution and the signed distance map of the points inside and outside the object of interest are accurately estimated by modelling the empirical density function with a linear combination of discrete Gaussians (LCDG) with positive and negative components. Experimental results on the segmentation of the kidneys from low-contrast DCE-MRI and on the segmentation of the ventricles from brain MRFs show how the approach is accurate in segmenting 2-D and 3-D data sets. The 2D results for the kidney segmentation have been validated by a radiologist and the 3D results of the ventricle segmentation have been validated with a geometrical phantom. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image segmentation

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Variational-based method to extract parametric shapes from images

Variational-based method to extract parametric shapes from i...

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Proceedings - 10th IEEE International Conference on computer vision, ICCV 2005

作者： El-Melegy, Moumen T. Al-Ashwal, Nagi H. Farag, Aly A. Electrical Engineering Department Assiut University Assiut 71516 Egypt Computer Vision and Image Processing Lab. University of Louisville KY 40292

ISBN: (纸本)076952334X

In this paper, we propose a variational method to segment image objects, which have a given parametric shape based on a level-set formulation of the Mumford-Shah functional, and the shape parameters. We define an energy functional composed by two complementary terms. The first one detects object boundaries using a Chan-Vese-like method. The second term constrains the contour to find a shape compatible with the parametric shape. The segmentation of the object of interest is given by the minimum of our energy functional. This minimum is computed with the calculus of variation and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. We focus in this paper on the parametric category of image linear objects. Applications of the proposed model are presented on synthetic and real images. © 2005 IEEE.

关键词： image segmentation

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3D path planning for virtual endoscopy

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International Congress Series 2005年 1281卷 115-120页

作者： Hassouna, M. Sabry Farag, A.A. Hushek, Stephen G. Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY 40292 United States iMRI Department Norton Hospital Louisville KY 40202 United States

Centerline extraction of curvilinear objects is a crucial component of virtual endoscopy (VE) because it provides path planning for automatic navigation. In this paper, we present a guided voxel coding (GVC) algorithm that modifies the original method to extract reliable centerlines suitable for fly-through applications. Our proposed method extracts potential centerline voxels with maximal spheres inscribed in the object and stores them in an a priori guidance map. Centerlines are initially extracted as trajectories inside the object and then centered using a new mechanism that exploits the information contained in that map. A new level set method accurately identifies the topological branching nodes of the joint centerlines. Finally, a thinning method is proposed to guarantee single voxel width centerlines. The proposed algorithm is completely automated and generates reliable, connected, and smoothed navigation paths for complex tree structures. © 2005.

关键词： 3D path planning Flight path generation Virtual endoscopy

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