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International Conference on Optimization of electrical and Electronic Equipment, OPTIM

作者： C. Vertan V. Buzuloiu R.M. Rangayyan Image Processing and Analysis Laboratory (IPAL) Applied Electronics and Information Engineering DepartmentFaculty of Electronics and Telecommunications Politehnica University Bucharest Romania Department of Electrical and Computer Engineering University of Calgary Calgary AB Canada

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Training environment for inferior vena caval filter placement

Training environment for inferior vena caval filter placemen...

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6th Conferenc on Medicine Meets Virtual Reality, MMVR 1998

作者： Hahn, James K. Kaufman, Roger Winick, Adam B. Carleton, Thurston Park, Youngser Lindeman, Rob Oh, Kwang-Man Ai-Ghreimil, Nadia Walsh, Raymond J. Loew, Murray Gerber, Joanne Sankar, Siddarth Laboratory for Advanced Computer Applications in Medicine Institute for Computer Graphics George Washington University Washington DC 20052 United States Department of Electrical Engineering and Computer Science George Washington University Washington DC 20052 United States Department of Radiology George Washington University Washington DC 20052 United States Department of Civil and Mechanical Engineering George Washington University Washington DC 20052 United States Department of Anatomy and Cell Biology George Washington University Washington DC 20052 United States Institute for Medical Imaging and Image Analysis George Washington University Washington DC 20052 United States

ISBN: (纸本)9051993862

This paper describes a Virtual Environment system designed to aid in training interventional radiologists in inferior vena cava filter placement. It is being developed as part of a VE simulator for a number of surgical and interventional radiology procedures at the laboratory for Advanced computer Applications in Medicine at the George Washington University. In this procedure a filter is placed in the inferior vena cava to prevent blood clots from the lower portion of the body from reaching the lungs and causing a pulmonary embolus. The simulation is designed to provide both tutorial and testing modes for the filter placement procedure.

关键词： Virtual reality

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1.5V resistive fuse for image smoothing and segmentation

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ELECTRONICS LETTERS 1997年第10期33卷 851-852页

作者： Athreya, JKV Gregson, PH Department of Electrical Engineering Computer Vision and Image Processing Laboratory Technical University of Nova Scotia Halifax Canada

A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage;it switches off if the differential voltage is higher than the set value. The useful operation range of the circuit is 0.4V with a supply voltage of 1.5V and threshold voltages of V-Tn = 0.828V and V-Tp = -0.56V for n and g channel MOSFETs, respectively.

关键词： image processing segmentation (image processing)

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Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Ahmed, MN Farag, AA Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)0780341236

In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be apdated to real-time imaging scenarios.

关键词： segmentation pattern analysis learning in vision

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3D reconstruction of the human jaw from a sequence of images

3D reconstruction of the human jaw from a sequence of images

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Conference on computer vision and Pattern Recognition (CVPR)

作者： M. Ahmed S. Yamany E. Hemayed S. Ahmed S. Roberts A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

关键词： image reconstruction Humans computer vision Data acquisition Cameras Shape Data mining Genetic algorithms Implants Machine vision

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Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

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International Conference on Neural Networks

作者： M.N. Ahmed A.A. Farag Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Louisville Louisville KY USA

We present a system to segment and label CT/MRI brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be adapted to real-time imaging scenarios.

关键词： Neural networks image segmentation Biomedical imaging Feature extraction Principal component analysis Computed tomography Magnetic resonance imaging Brain Labeling Clustering algorithms

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Reconstruction of vector fields in bounded domain vector tomography

Reconstruction of vector fields in bounded domain vector tom...

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IEEE International Conference on image Processing

作者： N.F. Osman J.L. Prince Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

This paper considers the problem of vector tomography on an arbitrary bounded domain in three dimensions. Previous work has given the formulas for the reconstructed scalar and vector potential functions in relation to the vector field values inside the domain and on the boundary of the domain. Using these formulas. It is shown that the curl-free component can be reconstructed using only one probe measurement, and the divergence-free component can be reconstructed using only two probe measurements. No boundary measurements are necessary.

关键词： Tomography Probes image reconstruction Magnetic field measurement Magnetic materials image analysis Laboratories Doppler measurements Magnetic resonance imaging Acoustic measurements

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Morphologically constrained Gibbs random fields

Morphologically constrained Gibbs random fields

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IEEE International Conference on image Processing

作者： K. Sivakumar J. Goutsias Dept. of Electr. & Comput. Eng. Johns Hopkins Univ. Baltimore MD USA Image Analysis and Communications Laboratory Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

We propose a class of Gibbs random fields which incorporate geometric information into stochastic image modeling by means of morphological constraints. This class is shown to be capable of modeling shapes with given m... 详细信息

关键词： Stochastic processes Solid modeling Shape

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Editorial

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International Journal of Pattern Recognition and Artificial Intelligence 1997年第8期11卷 1157-1160页

作者： W. C. Karl D. N. Kennedy A. J. Worth H. H. Pien A. S. Willsky Department of Electrical and Computer Engineering Boston University Boston MA 02215 USA Center for Morphometric Analysis Massachusetts General Hospital Charlestown MA 02129 USA Image Recognition Systems Draper Laboratory Cambridge MA 02139 USA Center for Morphometric Analysis Neuroscience Center Massachusetts General Hospital-East Building 149 13th St. Charlestown MA 02129-2000 USA

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Convolution backprojection formulas for 3-D vector tomography with application to MRI

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IEEE TRANSACTIONS ON image PROCESSING 1996年第10期5卷 1462-1472页

作者： Prince, JL Department of Electrical and Computer Engineering Image Analysis and Communications Laboratory The Johns Hopkins tlniversity

Vector tomography is the reconstruction of vector fields from measurements of their projections, In previous work, it has been shown that reconstruction of a general three-dimensional (3-D) vector field is possible from the so-called inner product measurements, It has also been shown how reconstruction of either the irrotational or solenoidal component of a vector field can be accomplished with fewer measurements than that required for the full field, The present paper makes three contributions. First, in analogy to the two-dimensional (2-D) approach of Norton, several 3-D projection theorems are developed. These lead directly to new vector field reconstruction formulas that are convolution backprojection formulas, It is shown how the local reconstruction property of these 3-D reconstruction formulas permits reconstruction of point flow or of regional flow from a limited data set, Second, simulations demonstrating 3-D reconstructions, both local and nonlocal, are presented, Using the formulas derived herein and those derived in previous work, these results demonstrate reconstruction of the irrotational and solenoidal components, their potential functions, and the field itself from simulated inner product measurement data, Finally, it is shown how 3-D inner product measurements can be acquired using a magnetic resonance scanner.

关键词： backprojection Dot product potential function Convolution formula Three Dimensions Vector field irrotational three-dimensional displays

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