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Conference on Medical Imaging 2011 - Visualization, Image-Guided Procedures, and Modeling

作者： Lang, Pencilla Seslija, Petar Bainbridge, Daniel Guiraudon, Gerard M. Jones, Douglas L. Chu, Michael W. Holdsworth, David W. Peters, Terry M. Robarts Res Inst London England Univ Western Ontario Biomed Engn Grad Program London ON N6A 3K7 Canada Canadian Surg Technol & Adv Robot London England Univ Western Ontario Dept Med London ON N6A 3K7 Canada London Hlth Sci Ctr London ON Canada Univ Western Ontario Div Cardiac Surgery London ON N6A 3K7 Canada

ISBN: (纸本)9780819485069

This study assesses the accuracy of a new transesophageal (TEE) ultrasound (US) fluoroscopy registration technique designed to guide percutaneous aortic valve replacement. In this minimally invasive procedure, a valve is inserted into the aortic annulus via a catheter. Navigation and positioning of the valve is guided primarily by intra-operative fluoroscopy. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to heart valve embolization, obstruction of the coronary ostia and acute kidney injury. The use of TEE US images to augment intra-operative fluoroscopy provides significant improvements to image-guidance. Registration is achieved using an image-based TEE probe tracking technique and US calibration. TEE probe tracking is accomplished using a single-perspective pose estimation algorithm. Pose estimation from a single image allows registration to be achieved using only images collected in standard OR workflow. Accuracy of this registration technique is assessed using three models: a point target phantom, a cadaveric porcine heart with implanted fiducials, and in-vivo porcine images. Results demonstrate that registration can be achieved with an RMS error of less than 1.5mm, which is within the clinical accuracy requirements of 5mm. US-fluoroscopy registration based on single-perspective pose estimation demonstrates promise as a method for providing guidance to percutaneous aortic valve replacement procedures. Future work will focus on real-time implementation and a visualization system that can be used in the operating room.

关键词： Fluoroscopy Image registration Ultrasonography Heart Calibration Visualization Computed tomography 3D modeling In vivo imaging detection and tracking algorithms

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SPARSE DUAL FRAMES IN COMPRESSED SENSING

SPARSE DUAL FRAMES IN COMPRESSED SENSING

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Conference on Wavelets and Sparsity XIV

作者： Li, Shidong Mi, Tiebin Liu, Yulong San Francisco State Univ Dept Math San Francisco CA 94132 USA Renmin Univ China Sch Informat Beijing Peoples R China

ISBN: (纸本)9780819487483

A notion of sparse dual frames for a given non-exact frame is introduced. The sparse dual frame is motivated in a study of compressed sensing problems where signal are sparse with respect to a redundant and coherent dictionary (frames). A sparse-dual-based l(1)-analysis is thereby proposed. We show that sparse dual frames are locally stable. An error bound ensuring the correct signal recovery is obtained. More importantly, solutions to very hard problems in compressed sensing with redundant dictionaries that are otherwise completely unsuccessful by known algorithms of l(1)-synthesis and the l(1)-analysis are seen as satisfactory, by the new sparse-dual-based approach and an alternating iterative algorithm that we propose. Examples are provided.

关键词： Compressed sensing Error analysis Associative arrays Atrial fibrillation Algorithm development Chemical elements detection and tracking algorithms Radon Seaborgium Ultraviolet radiation

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A Butterfly Algorithm for Synthetic Aperture Radar

A Butterfly Algorithm for Synthetic Aperture Radar

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Conference on algorithms for Synthetic Aperture Radar Imagery XVIII

作者： Demanet, Laurent Ferrara, Matthew Maxwell, Nicholas Poulson, Jack Ying, Lexing MIT Dept Math Cambridge MA 02139 USA Matrix Res Inc Dayton OH USA Univ Houston Dept Math Houston TX USA Univ Texas Austin ICES Austin TX USA Univ Texas Austin Dept Math Austin TX USA

ISBN: (纸本)9780819486257

It is not currently known if it is possible to accurately form a synthetic aperture radar image from N data points in provable near-linear complexity, where accuracy is defined as the l(2) error between the full O(N-2) backprojection image and the approximate image. To bridge this gap, we present a backprojection algorithm with complexity O(log(1/c) N log N), with c the tunable pixelwise accuracy. It is based on the butterfly scheme, which works for vastly more general oscillatory integrals than the discrete Fourier transform. Unlike previous methods this algorithm allows the user to directly choose the amount of acceptable image error based on a well-defined metric. Additionally, the algorithm does not invoke the far-field approximation or place restrictions on the antenna flight path, nor does it impose the frequency-independent beampattern approximation required by time-domain backprojection techniques.

关键词： Antennas Synthetic aperture radar Data modeling Fourier transforms Error analysis detection and tracking algorithms Mathematics Scattering algorithms Bridges

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Conference on Imaging and Printing in a Web 2.0 World II

作者： Ahmadullin, Ildus Fan, Jian Damera-Venkata, Niranjan Lim, Suk Hwan Lin, Qian Liu, Jerry Liu, Sam O'Brien-Strain, Eamonn Allebach, Jan Purdue Univ W Lafayette IN 47907 USA Hewlett Packard Labs Palo Alto CA 94304 USA

ISBN: (纸本)9780819484161

Managing large document databases is an important task today. Being able to automatically compare document layouts and classify and search documents with respect to their visual appearance proves to be desirable in many applications. We measure single page documents' similarity with respect to distance functions between three document components: background, text, and saliency. Each document component is represented as a Gaussian mixture distribution;and distances between different documents' components are calculated as probabilistic similarities between corresponding distributions. The similarity measure between documents is represented as a weighted sum of the components' distances. Using this document similarity measure, we propose a browsing mechanism operating on a document dataset. For these purposes, we use a hierarchical browsing environment which we call the document similarity pyramid. It allows the user to browse a large document dataset and to search for documents in the dataset that are similar to the query. The user can browse the dataset on different levels of the pyramid, and zoom into the documents that are of interest.

关键词： Visualization Databases Expectation maximization algorithms Image segmentation Zoom lenses Darmstadtium Dubnium Feature extraction detection and tracking algorithms RGB color model

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Effects of Random Measurements on the Performance of Target detection in Hyperspectral Imagery

Effects of Random Measurements on the Performance of Target ...

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

作者： Chen, Yi Nasrabadi, Nasser M. Tran, Trac D. Johns Hopkins Univ Dept Elect & Comp Engn 3400 N Charles St Baltimore MD 21218 USA US Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9780819486226

Hyperspectral pixels are acquired in hundreds of narrow and continuous spectral bands, and the hyperspectral data cubes typically contain hundreds of megabytes. Analysis and processing of the high-dimensional hyperspectral data are computationally expensive and memory inefficient. However, there is a large amount of redundancy between neighboring spectral bands and the hyperspectral pixels lie in a much lower dimensional subspace. Therefore, numerous techniques can be applied to reduce the dimensionality while maintaining the structure of the data. This would lead to a significant reduction of the complexity of the imaging system, as well as an improvement of the computational efficiency of the detection algorithms. In this paper, we explore the use of several dimensionality reduction techniques that can be easily integrated into the imaging sensors. We also investigate their effect on the performance of classical target detection techniques for hyperspectral images, including spectral matched filters (SMF), matched subspace detectors (MSD), support vector machines (SVM), and RX anomaly detection algorithm. Specifically, each N-dimensional spectral pixel is embedded to an M-dimensional measurement space with M << N by a linear transformation (e.g., random measurement matrices, uniform downsampling, PCA). The SMF, MSD, SVM, and RX detectors are then applied to the M-dimensional measurement vectors to detect the targets of interests and their detection performances are compared to those obtained from the entire N-dimensional spectrum by the receiver operating characteristics curves. Through extensive experiments on several HSI datasets, we demonstrate that only 1/5 to 1/3 measurements (i.e., the compression ratio M/N is 1/5 similar to 1/3) are necessary to achieve detection performance comparable to that obtained by exploiting the full N-dimensional pixels.

关键词： Single mode fibers Target detection Sensors Matrices Principal component analysis detection and tracking algorithms Hyperspectral imaging Hyperspectral target detection Optical sensors Optical filters

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Quality of Arabic Utterances Transformed Using Different Residual Prediction Techniques

Quality of Arabic Utterances Transformed Using Different Res...

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International Conference on Graphic and Image Processing (ICGIP)

作者： Elmanfaloty, Rania Korany, N. Youssef, El-Sayed A. Fac Engn Alexandria Dept Elect Engn Alexandria Egypt

ISBN: (纸本)9780819489326

Voice conversion (VC) is a process which modifies the speech signal produced by one source speaker so that it sounds like another target speaker. In this paper the transformation is determined by using equal Arabic utterances from source and target speakers;these utterances are time-aligned using dynamic time warping algorithm. A conversion function based on Gaussian mixture model (GMM) is used for transforming the spectral envelope described by line spectral frequencies (LSF) and the residuals are converted using three residual prediction techniques. We also compare between these techniques in the conversion of some Arabic utterances. The quality of the transformed utterances is measured using subjective and objective evaluations.

关键词： Signal to noise ratio Molybdenum Signal processing Virtual colonoscopy Data conversion Data modeling detection and tracking algorithms Electrical engineering Image processing Visualization

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Efficient Exchange of Information in a Distributed tracking Environment

Efficient Exchange of Information in a Distributed Tracking ...

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Conference on Signal Processing, Sensor Fusion, and Target Recognition XX

作者： Shea, Peter J. Blake, Eric Black River Syst Co Lakeville MN 55044 USA

ISBN: (纸本)9780819486240

Modern tracking and fusion settings involve multiple platforms in different locations, tracking different target tracks, focusing on different regions of interest, while using different update rates and sensor resolutions with the goal of providing increased situation awareness in the region by fusing together the diversity of information from each platform. In this paper, a decentralized, distributed fusion architecture is presented along with results and trade studies comparing performance to that of a centralized fusion architecture. The decentralized distributed architecture is designed to work with legacy tracking systems and uses an efficient message passing scheme to share information and coordinate tracks across a diverse group of platforms. This system does not rely on a central node and allows for track information to be maintained at the local level while utilizing track information from other platforms to increase situation awareness. We compare the performance between our distributed approach and a centralized system using simulated airborne sensors operating in overlapping regions of interest with target densities and routes chosen to demonstrate tradeoffs between the different architectures. Preliminary results show that the decentralized distributed system provides similar performance to the centralized fusion system in terms of situation awareness relative to traditional tracking metrics, but at the cost of using an increased communication bandwidth to provide frequent updates to neighboring platforms. Results demonstrate the tradeoff between flexibility and optimality - configuration of the distributed decentralized system to provide increased flexibility and robustness comes at the cost of reduced situation awareness as compared to the centralized system.

关键词： Sensors Data transmission Computer architecture detection and tracking algorithms Distributed computing Surveillance Target detection Computer simulations Telecommunications Network architectures

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Unusual event detection and prediction based on sectional contextual edit distance

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JOURNAL OF ELECTRONIC IMAGING 2010年第1期19卷 013009-013009-8页

作者： Zhang, Yi Yang, Jie Liu, Kun Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200240 Peoples R China

We redefine the unusual event detection problem from a different point of view. Several fundamental event features are investigated and adopted. These features are redescribed in a uniform model. Thus, using this model, supervised/unsupervised unusual event detection algorithms can be designed to fit various situations. Trajectory is treated as the most important feature. To more accurately measure the similarity of different moving object trajectories, a novel distance measurement, the sectional contextual edit distance ( SCED), is developed. In the SCED, cost functions are designed according to contextual information and trajectories are segmented into subsections automatically, based on the relevant contexts. Velocity and orientation are also taken into account in cost functions to build an integrated distance similarity measurement. Experimental results demonstrate better performance using the newly proposed similarity measurement while being compared with the existing methods, and some cases of the unusual event detection problem are also demonstrated. (C) 2010 SPIE and IS&T. [DOI: 10.1117/1.3327951]

关键词： detection and tracking algorithms Distance measurement Modeling Machine learning Video Databases

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Stylometrics of artwork: uses and limitations

Stylometrics of artwork: uses and limitations

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Conference on Computer Vision and Image Analysis of Art

作者： Hughes, James M. Graham, Daniel J. Rockmore, Daniel N. Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA Dartmouth Coll Dept Math Hanover NH 03755 USA

ISBN: (纸本)9780819479242

A number of digital image analysis techniques have been developed in recent years to address art historical questions. These techniques allow non-destructive analyses of art images that can target outstanding problems of attribution, historical ordering, and other stylistic dimensions. However, great care must be taken in designing the comparisons to which these techniques are applied. In this paper, we review recent work by our lab and by others aimed at establishing a toolbox of stylometrics, and we discuss some of the uses and limitations of these methods. We describe a technique that provides robust classification of authentic drawings by Pieter Bruegel the Elder, and we demonstrate new techniques for art historical analysis applied to the works of other masters. Specifically, we demonstrate the use of two low-level statistics (the slope of the log amplitude spectrum and color histogram correlation) to analyze the works of Picasso and Braque. Finally, we show that face detection and recognition techniques may play a useful role in the attribution of works of art. The rationale for employing vision coding-like methods (e. g., sparse coding) in stylometry is also reviewed. We conclude that generic authentication tools are unlikely to provide reliable stylometric predictions but that with careful construction of comparison sets - which we believe must be done in close collaboration with art historians - these techniques provide important predictions that can be weighed against other art historical evidence. We argue further that concurrent predictions derived from analysis of many independent dimensions of image data (e. g., color, luminance, and spatial statistics) provide the strongest evidence for digital stylometric determinations.

关键词： Facial recognition systems Statistical analysis Image analysis detection and tracking algorithms Analytical research Image compression RGB color model Image filtering Nondestructive evaluation Statistical modeling

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CPHD filtering with unknown probability of detection

CPHD filtering with unknown probability of detection

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Conference on Signal Processing, Sensor Fusion, and Target Recognition XIX

作者： Mahler, Ronald El-Fallah, Adel Lockheed Martin MS2 Eagan MN 55121 USA Sci Syst Co Inc Huntsville AL USA

ISBN: (纸本)9780819481610

The conventional PHD and CPHD filters presume that the probability p(D)(x) that a measurement will be collected from a target with state-vector x (the state-dependent probability of detection) is known a priori. However, in many applications this presumption is false. A few methods have been devised for estimating the probability of detection, but they typically presume that p(D)(x) is constant in both time and the region of interest. This paper introduces CPHD/PHD filters that are capable of multitarget track-before-detect operation even when probability of detection is not known and, moreover, when it is not necessarily constant, either temporally or spatially. Furthermore, these filters are potentially computationally tractable. We begin by deriving CPHD/PHD filter equations for the case when probability of detection is unknown but the clutter model is known a priori. Then, building on the results of a companion paper, we note that CPHD/PHD filters can be derived for the case when neither probability of detection or the background clutter are known.

关键词： Sensors Target detection Radar Superposition Current controlled current source detection and tracking algorithms Environmental sensing Sensor fusion Signal processing Target recognition

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