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Two-stage neural network for volume segmentation of medical images

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

引用

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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Temporal prediction of video sequences using an image warping technique based on color segmentation 9th

Temporal prediction of video sequences using an image warpin...

引用

9th International Conference on image Analysis and processing, ICIAP 1997

作者： Herodotou, N. Venetsanopoulos, A.N. Digital Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of Toronto 10 King's College Road TorontoONM5S 3G4 Canada

ISBN: (纸本)3540635076

An image warping technique based on segmented regions is introduced for the temporal prediction of videophone-type sequences. At the encoder, a set of control points are determined from the previous frame and their corresponding best matched points are determined from the current frame. The selection process of these points is achieved by segmenting the previous frame into different regions using a color segmentation technique based on a recursive histogramming approach and the control points are subsequently chosen along the region boundaries. The spatial offset of these points between the previous and current frame are represented as motion vectors. The facial area is intraframe encoded to avoid distortions of the facial features which convey critical information. At the decoder, the same segmentation and control point selection algorithm is used along with the motion vectors in order to find the region boundaries of the predicted frame. The facial area is decoded and an affine transformation is finally used to determine the remaining regions and form the predicted frame. This technique produces results that are free from blocking artifacts as in the conventional block matching method, with only a moderate increase in computational complexity. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Decoding

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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

引用

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 ...

引用

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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Convergence considerations in moment-method analysis of a class of microstrip antennas

Convergence considerations in moment-method analysis of a cl...

引用

Antennas and Propagation Society International Symposium

作者： D. Chatterjee R.G. Plumb Radar Systems and Remote Sensing Laboratory Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

Inclusion of the probe-to-patch attachment mode current in the full-wave analysis of probe-fed microstrip antennas showed superior agreement with input impedance measurements. The attachment mode can be represented by the infinite eigenfunction or residue series, which are mutually different across the Stokes regions. It is shown that the residue series has better convergence properties and hence can be used to develop efficient moment-method algorithms for such antenna configurations.

关键词： Microstrip antennas Convergence Eigenvalues and eigenfunctions Geometry Radar antennas Impedance measurement Green's function methods Radar measurements Radar remote sensing remote sensing

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Artificial neural network-based inversion technique for extracting ocean surface wave spectra from SAR images

Artificial neural network-based inversion technique for extr...

引用

IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： D. Kasilingam Jian Shi Centre for Remote Imaging Sensing and Processing National University of Singapore Singapore Singapore Department of Electrical and Computer Engineering University of Massachusetts North Dartmouth MA USA

An artificial neural network (ANN) based nonlinear technique for inverting the SAR image spectrum of ocean surface waves is developed. In this technique, a multi-layer perceptron (MLP) is used to perform the inversion process. The MLP is trained using simulated SAR and wave spectra. The training process utilizes the standard error-backpropagation technique. The results indicate that the method works well over a large range of wind and wave conditions. The error in the inversion process was found to increase in the higher sea states. The technique works best if the network is used within the range over which it was trained. It is noted that this technique may be used independent of SAR imaging models, by training the network with coincident and co-located measurements of SAR and wave spectra.

关键词： Artificial neural networks Oceans Surface waves Sea surface Sea measurements Extraterrestrial measurements Rough surfaces Surface roughness Radar polarimetry Synthetic aperture radar

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Effect of azimuth bandwidth spreading on SAR imaging and SAR interferometry over the ocean

Effect of azimuth bandwidth spreading on SAR imaging and SAR...

引用

IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Baosen Zhou D. Kasilingam Department of Electrical and Computer Engineering University of Massachusetts Dartmouth North Dartmouth MA USA Centre for Remote Imaging Sensing and Processing National University of Singapore Singapore

Radar backscatter measurements over the ocean, from a L-band, tower-based radar are used to study the effect of bandwidth spreading on SAR imaging systems and SAR interferometry. The coherent radar measurements are put through a SAR simulator to generate the image of the radar footprint on the ocean surface. This simulated SAR image is analyzed for resolution and phase coherence. It is shown that as the SAR integration time is increased from near zero, the resolution will improve initially. However, increasing the integration time beyond the scene coherence time will have little impact on the resolution. It also shown that in SAR interferometry, increasing the integration time degrades the phase resolution. Optimum values of integration times and interferometric time delays are suggested for SAR imaging and along-track interferometry, respectively.

关键词： Azimuth Bandwidth Radar polarimetry Radar measurements Radar imaging Interferometry Oceans Synthetic aperture radar Backscatter Sea measurements

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Model-based detection and correction of corrupted wavelet coefficients

Model-based detection and correction of corrupted wavelet co...

引用

IEEE International Conference on image processing

作者： N. Strobel S.K. Mitra B.S. Manjunath Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara USA University of California Santa Barbara Santa Barbara CA US

image decomposition based on the discrete wavelet transform (DWT) has been proposed for efficient storage and progressive transmission of images for visual browsing in digital image libraries. Although the compression aspects of the DWT have been carefully researched, reconstruction errors due to corrupted wavelet coefficients have received less attention. In this paper we consider the problem of bit errors affecting uniformly quantized wavelet coefficients. The proposed method, which is based on a local image model, simultaneously detects and masks corrupted wavelet coefficients.

关键词： Wavelet coefficients image coding image reconstruction Discrete wavelet transforms Filters Decoding Error correction image edge detection Signal processing image processing

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The contrast pyramid based image code

The contrast pyramid based image code

引用

IEEE International Conference on image processing

作者： Tian-Hu Yu Jianhua Chen S.K. Mitra Department of Information Engineering Chinese University of Hong Kong New Territories Hong Kong China Department of Electrical and Computer Engineering Signal and Image Processing Laboratory University of California Santa Barbara CA USA

In this paper, a contrast pyramid based image coding method is described in which a simple nonlinear difference operation is introduced to generate residual information between two contiguous level images. The representation of the residual information can be considered as a local contrast measure. As the difference image in established pyramid coding techniques, the contrast image has low variance, and data compression is achieved by quantizing the contrast image. Based on Weber's law and spatial masking of the human visual system, further data compression can be attained by selecting only perceptually significant information from the contrast image and coding it efficiently.

关键词： image coding Laplace equations Low pass filters Data compression Humans Data structures Nonlinear filters Filtering image generation Visual system

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Three-dimensional analytical and numerical solutions for acousto-optic interaction

Three-dimensional analytical and numerical solutions for aco...

引用

Southeastern Symposium on System Theory

作者： D.B. Dunn M. McNeill Jiangang Xia Ting-Chung Poon P.P. Banerjee Optical Image Processing Laboratory The Bradley Department of Electrical Engineering Virginia Polytechnic Institute and State University VA USA Department of Elec. Engineering Bucknell University USA York University Canada Center for Applied Optics Department of Electrical and Computer Engineering University of Alabama Huntsville Huntsville AL USA

The authors present an analytical solution to the strong acousto-optic interaction problem in three dimensions. They then compare the analytical results to a split-step numerical algorithm. The algorithm is based on t... 详细信息

关键词： Optical propagation Acoustic beams Transfer functions Diffraction Acoustic propagation USA Councils Gratings image analysis image processing Laboratories

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