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检索条件"主题词=Expectation maximization algorithms"

共 128 条记录，以下是111-120 订阅

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K-Means Re-Clustering - algorithmic options with quantifiable performance comparisons

K-Means Re-Clustering - algorithmic options with quantifiabl...

引用

Conference on Optical Engineering at the Lawrence-Livermore-National-Laboratory

作者： Meyer, A Paglieroni, D Astaneh, C Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)081944801X

This paper presents various architectural options for implementing a K-Means Re-Clustering algorithm suitable for unsupervised segmentation of hyperspectral images. Performance metrics are developed based upon quantitative comparisons of convergence rates and segmentation quality. A methodology for making these comparisons is developed and used to establish K values that produce the best segmentations with minimal processing requirements. Convergence rates depend on the initial choice of cluster centers. Consequently, this same methodology may be used to evaluate the effectiveness of different initialization techniques.

关键词： Image segmentation expectation maximization algorithms Image processing algorithms and systems Algorithm development Image quality Spectral resolution Hyperspectral imaging Image classification Quantization Image processing

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A Deep Kernel Method for PET Image Reconstruction

A Deep Kernel Method for PET Image Reconstruction

引用

Conference on Medical Imaging - Image Processing

作者： Li, Siqi Wang, Guobao Univ Calif Davis Med Ctr Dept Radiol Sacramento CA 95817 USA

ISBN: (数字)9781510649408

ISBN: (纸本)9781510649408;9781510649392

Image reconstruction for positron emission tomography (PET) is challenging because of the ill-conditioned tomographic problem and low counting statistics. Kernel methods address this challenge by using kernel representation to incorporate image prior information in the forward model of iterative PET image reconstruction. Existing kernel methods construct the kernels commonly using an empirical procedure, which may lead to suboptimal performance. In this paper, we describe the equivalence between the kernel representation and a trainable neural network model. A deep kernel method is proposed with the training process utilizing available image prior to seek the best way to form a set of robust kernels optimally rather than empirically. The results from computer simulations and a real patient dataset demonstrate that the proposed deep kernel method can outperform existing kernel method and neural network method for dynamic PET image reconstruction.

关键词： Positron emission tomography Data modeling Image restoration Neural networks Reconstruction algorithms expectation maximization algorithms Signal to noise ratio Feature extraction Image processing Computer simulations

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An adaptive index structure for similarity search in large image databases

An adaptive index structure for similarity search in large i...

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Conference on Internet Multimedia Management Systems II

作者： Wu, P Manjunath, BS Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)0819442437

A practical method for creating a high dimensional index structure that adapts to the data distribution and scales well with the database size, is presented. Typical media descriptors, such as texture features, are high dimensional and are not uniformly distributed in the feature space. The performance of many existing methods degrade if the data is not uniformly distributed. The proposed method offers an efficient solution to this problem. First, the data's marginal distribution along each dimension is characterized using a Gaussian mixture model. The parameters of this model are estimated using the well known expectation-maximization (EM) method. These model parameters can also be estimated sequentially for on-line updating. Using the marginal distribution information, each of the data dimensions can be partitioned such that each bin contains approximately an equal number of objects. Experimental results on a real image texture data set are presented. Comparisons with existing techniques, such as the well known VA-File, demonstrate a significant overall improvement.

关键词： Databases Data modeling expectation maximization algorithms Distance measurement Nickel Quantization Algorithm development Data analysis Multimedia Computer engineering

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TOMOGRAPHIC TECHNIQUES IN IMAGE AND SIGNAL-PROCESSING

TOMOGRAPHIC TECHNIQUES IN IMAGE AND SIGNAL-PROCESSING

引用

CONF ON ADVANCED SIGNAL-PROCESSING algorithms, ARCHITECTURES, AND IMPLEMENTATIONS

作者： SNYDER, DL Washington Univ. (United States)

An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.

ISBN: (纸本)0819404098

An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging.

关键词： Tomography expectation maximization algorithms Signal processing Image processing Reconstruction algorithms Imaging systems Detection and tracking algorithms Sensors Stochastic processes Image filtering

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Adaptive constrained signal detector for hyperspectral images

Adaptive constrained signal detector for hyperspectral image...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII

作者： Johnson, Steven E. Eismann, Michael T. AF Inst Technol Wright Patterson AFB OH USA Air Force Res Lab Wright Patterson AFB OH USA

ISBN: (纸本)9780819466877

An algorithm called the constrained signal detector (CSD) was recently introduced for the purpose of target detection in hyperspectral images. The CSD assumes that hyperspectral pixels can be modeled as linear mixtures of material signatures and stochastic noise. In theory, the CSD is superior to the popular orthogonal subspace projection (OSP) technique. The CSD requires knowledge of the spectra of the background materials in a hyperspectral image. But in practice the background material spectra are often unknown due to uncertainties in illumination, atmospheric conditions, and the composition of the scene being imaged. In this paper, estimation techniques are used to create an adaptive version of the CSD. This adaptive algorithm uses training data to develop a description of the image background and adaptively implement the CSD. The adaptive CSD only requires knowledge of the target spectrum. It is shown through simulations that the adaptive CSD performs nearly as well as the CSD operating with complete knowledge of the background material spectra. The adaptive CSD is also tested using real hyperspectral image data and its performance is compared to OSP.

关键词： Signal detection Sensors Hyperspectral imaging Target detection Detection and tracking algorithms Hyperspectral target detection Signal to noise ratio Algorithm development expectation maximization algorithms Reflectivity

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Exploring the feasibility of traditional image querying tasks for industrial radiographs 5

Exploring the feasibility of traditional image querying task...

引用

Conference on Medical Applications of Radiation Detectors V

作者： Bray, Iliana E. Tsai, Stephany J. Jimenez, Edward S. Sandia Natl Labs Albuquerque NM 87185 USA

ISBN: (纸本)9781628417609

Although there have been great strides in object recognition with optical images (photographs), there has been comparatively little research into object recognition for X-ray radiographs. Our exploratory work contributes to this area by creating an object recognition system designed to recognize components from a related database of radiographs. Object recognition for radiographs must be approached differently than for optical images, because radiographs have much less color-based information to distinguish objects, and they exhibit transmission overlap that alters perceived object shapes. The dataset used in this work contained more than 55,000 intermixed radiographs and photographs, all in a compressed JPEG form and with multiple ways of describing pixel information. For this work, a robust and efficient system is needed to combat problems presented by properties of the X-ray imaging modality, the large size of the given database, and the quality of the images contained in said database. We have explored various pre-processing techniques to clean the cluttered and low-quality images in the database, and we have developed our object recognition system by combining multiple object detection and feature extraction methods. We present the preliminary results of the still-evolving hybrid object recognition system.

关键词： Object recognition Radiography X-rays Databases X-ray imaging Detection and tracking algorithms Image processing Image segmentation expectation maximization algorithms Photography

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Topologically Correct Cortical Segmentation using Khalimsky's Cubic Complex framework

Topologically Correct Cortical Segmentation using Khalimsky'...

引用

Conference on Medical Imaging 2011 - Image Processing

作者： Cardoso, Manuel Jorge Clarkson, Matthew J. Modat, Marc Talbot, Hugues Couprie, Michel Ourselin, Sebastien UCL Ctr Med Image Comp London WC1E 6BT England Univ Paris Est CNRS UMR 8049 A2SI ESIIEE Champs Sur Marne France

ISBN: (纸本)9780819485045

Automatic segmentation of the cerebral cortex from magnetic resonance brain images is a valuable tool for neuroscience research. Due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cerebral cortex, segmenting the brain in a robust, accurate and topologically correct way still poses a challenge. In this paper we describe a topologically correct expectation Maximisation based Maximum a Posteriori segmentation algorithm formulated within the Khalimsky cubic complex framework, where both the solution of the EM algorithm and the information derived from a geodesic distance function are used to locally modify the weighting of a Markov Random Field and drive the topology correction operations. Experiments performed on 20 Brainweb datasets show that the proposed method obtains a topologically correct segmentation without significant loss in accuracy when compared to two well established techniques.

关键词： expectation maximization algorithms Image segmentation Brain Algorithm development Independent component analysis Tissues Magnetorheological finishing Cerebral cortex Magnetic resonance imaging Surgery

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OBJECT DETECTION AND AMPLITUDE ESTIMATION BASED ON MAXIMUM A POSTERIORI RECONSTRUCTIONS 4

OBJECT DETECTION AND AMPLITUDE ESTIMATION BASED ON MAXIMUM A...

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CONF ON MEDICAL IMAGING 4 : IMAGE INFORMATION

作者： HANSON, KM Los Alamos National Lab. (United States)

We report on the behavior ofthe linear maximum a posteriori (MAP) tomographic reconstruction technique as a function of the assumed rms noise αn in the measurements, which specifies the degree of confidence ... 详细信息

ISBN: (纸本)0819402753

We report on the behavior ofthe linear maximum a posteriori (MAP) tomographic reconstruction technique as a function of the assumed rms noise α_n in the measurements, which specifies the degree of confidence in the measurement data. The unconstrained MAP reconstructions are evaluated on the basis of the performance of two related tasks; object detection and amplitude estimation. It is found that the detectability of medium-sized discs remains constant up to relatively large α_n before slowly diminishing. However, the amplitudes of the discs estimated from the MAP reconstructions increasingly deviate from their actual values as α_n increases.

关键词： Reconstruction algorithms Image acquisition Medical imaging Spatial frequencies Matrices expectation maximization algorithms Statistical analysis Lithium Tomography Monte Carlo methods

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SYSTEMATIC CONSTRUCTION OF ORDER-RECURSIVE LS ESTIMATION algorithms WITH ELEMENTARY ORTHOGONAL TRANSFORMATIONS 4

SYSTEMATIC CONSTRUCTION OF ORDER-RECURSIVE LS ESTIMATION ALG...

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4TH CONF ON ADVANCED SIGNAL PROCESSING algorithms, ARCHITECTURES, AND IMPLEMENTATIONS

作者： LING, F Motorola (United States)

ISBN: (纸本)0819412767

This paper demonstrates that order-recursive least squares (ORLS) algorithms based on orthogonal transformations and hyperbolic transformations can be systematically constructed in two steps. The first step is to determine the structure of the ORLS algorithm according to the property of the data vector in the LS estimation and the requirements to the output. The second step is to determine the proper implementation of building blocks of the ORLS structure using orthogonal or hyperbolic transformations. The canonical ORLS structure and some possible orthogonal/hyperbolic implementations of their building blocks are presented. It is also shown that some of the orthogonal transformations are only applicable to certain types of ORLS structures and not to others.

关键词： Algorithm development Error analysis Detection and tracking algorithms Digital signal processing expectation maximization algorithms Statistical analysis Factor analysis Magnesium Roads Telecommunications

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In search of Leonardo: Computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject

In search of Leonardo: Computer-based facial image analysis ...

引用

Conference on Human Vision and Electronic Imaging XVII

作者： Tyler, Christopher W. Smith, William A. P. Stork, David G. Smith Kettlewell Eye Res Inst 2318 Fillmore St San Francisco CA 94115 USA Univ York Dept Comp Sci York YO10 5DD N Yorkshire England Rambus Labs Sunnyvale CA 94089 USA

ISBN: (纸本)9780819489388

One of the enduring mysteries in the history of the Renaissance is the adult appearance of the archetypical "Renaissance Man," Leonardo da Vinci. His only acknowledged self-portrait is from an advanced age, and various candidate images of younger men are difficult to assess given the absence of documentary evidence. One clue about Leonardo's appearance comes from the remark of the contemporary historian, Vasari, that the sculpture of David by Leonardo's master, Andrea del Verrocchio, was based on the appearance of Leonardo when he was an apprentice. Taking a cue from this statement, we suggest that the more mature sculpture of St. Thomas, also by Verrocchio, might also have been a portrait of Leonardo. We tested the possibility Leonardo was the subject for Verrocchio's sculpture by a novel computational technique for the comparison of three-dimensional facial configurations. Based on quantitative measures of similarities, we also assess whether another pair of candidate two-dimensional images are plausibly attributable as being portraits of Leonardo as a young adult. Our results are consistent with the claim Leonardo is indeed the subject in these works, but we need comparisons with images in a larger corpora of candidate artworks before our results achieve statistical significance.

关键词： 3D modeling Cameras Data modeling Statistical analysis Image analysis Error analysis 3D image reconstruction Electronic imaging expectation maximization algorithms Statistical modeling

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