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Cross-Modality Assessment and Planning for Pulmonary Trunk Treatment Using CT and MRI Imaging

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13th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Vitanovski, Dime Tsymbal, Alexey Ionasec, Razvan Ioan Georgescu, Bogdan Huber, Martin Taylor, Andrew Schievano, Silvia Zhou, Shaohua Kevin Hornegger, Joachim Comaniciu, Dorin Siemens Corp Res Integrated Data Syst Princeton NJ 08540 USA Univ Erlangen Nurnberg Pattern Recognit Lab Nurnberg Germany Great Ormond St Hosp Sick Children London England

ISBN: (纸本)9783642157042

Congenital heart defect is the primary cause of death in new-borns, due to typically complex malformation of the cardiac system. The pulmonary valve and trunk are often affected and require complex clinical management and in most cases surgical or interventional treatment. While minimal invasive methods are emerging, non-invasive imaging-based assessment tools become crucial components in the clinical setting. For advanced evaluation and therapy planning purposes, cardiac Computed Tomography (CT) and cardiac Magnetic Resonance Imaging (cMRI) are important non-invasive investigation techniques with complementary properties. Although, characterized by high temporal resolution, cMRI does not cover the full motion of the pulmonary trunk. The sparse cMRI data acquired in this context include only one 3D scan of the heart in the end-diastolic phase and two 2D planes (long and short axes) over the whole cardiac cycle. In this paper we present a cross-modality framework for the evaluation of the pulmonary trunk, which combines the advantages of both, cardiac CT and cMRI. A patient-specific model is estimated from both modalities using hierarchical learning-based techniques. The pulmonary trunk model is exploited within a novel dynamic regression-based reconstruction to infer the incomplete cMRI temporal information. Extensive experiments performed on 72 cardiac CT and 74 cMRI sequences demonstrated the average speed of 110 seconds and accuracy of 1.4mm for the proposed approach. To the best of our knowledge this is the first dynamic model of the pulmonary trunk and right ventricle outflow track estimated from sparse 4D cMRI data.

关键词： Magnetic resonance imaging

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Weighted Total Variation constrained reconstruction for reduction of metal artifact in CT

Weighted Total Variation constrained reconstruction for redu...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Yanbo Zhang Xuanqin Mou Hao Yan Institute of Image Processing & Pattern Recognition Xi''an Jiaotong University Xi'an Shaanxi China

TV constrained reconstruction could obtain perfect results from incomplete data, and has been applied to reduce metal artifact by assuming that the projection contaminated by metal is missing. In TV constrained reconstruction, the selection of a proper step parameter for TV minimization procedure is a key point. However, this parameter is usually selected empirically, and it is a constant for all pixels in the whole image domain, regardless of the difference of missing projection quantity at different pixels. By analyzing the relationship between the missing projections and pixels position, a Weighted Total Variation (WTV) constrained reconstruction method is proposed to reduce metal artifact in this paper. For WTV constrained method, the parameters are no longer the same, but vary over image domain as the introduced information miss rate. The simulation results show that the proposed method is more effective than current TV constraint to reduce metal artifact. Moreover, WTV constrained method is extended to other incomplete projection problems.

关键词： TV image reconstruction Metals Pixel Computed tomography X-ray imaging Noise

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Perceptual grouping for building recognition from satellite SAR image stacks

Perceptual grouping for building recognition from satellite ...

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International conference on Pattern Recognition

作者： Michaelsen, E. Soergel, U. Schunert, A. Doktorski, L. Jaeger, Klaus Fraunhofer-IOSB Gutleuthausstrasse 1 76275 Ettlingen Germany IPI Leibniz Univ. Hannover Nienburger Str.1 30167 Hannover Germany

ISBN: (纸本)9781424472574

Modern high resolution satellite SAR sensors even allow analysis of building sub-structures like windows and balconies. In the amplitude data man-made objects usually appear either as salient bright lines or points embedded within dark background. The latter features may coincide also with so-called persistent scatterers (PS), whose phase history is exploited by time series analysis for 3D reconstruction and deformation monitoring. We apply principles of human gestalt perception for grouping urban objects such as entire facades. The analysis takes place both in the amplitude and the phase data. Fusion is possible at different levels, e.g: i) grouping results in one domain may focus search in the other domain, ii) both approaches allow to infer independently the 3D structure by exploiting complementary features (amplitude vs. phase), and iii) grouping as such is useful to introduce model knowledge. © 2010 IEEE.

关键词： Time series analysis

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Missing data imputation based on compressive sensing for robust speaker identification

Missing data imputation based on compressive sensing for rob...

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International conference on Wireless Communications and Signal Processing (WCSP)

作者： Xianyi Rui School of Electronic & Information Soochow University Suzhou China

In this paper, the method of missing data imputation based on the emergent field of compressive sensing for the front end of a speaker identification system in noisy conditions is investigated. Firstly, noisy speech signals are transformed into Gammatone spectrum by using cochlear filtering; then, unreliable spectral components are reconstructed given an incomplete set of reliable ones; finally, speaker features with auditory model are extracted from reconstructed Gammatone spectral data. Experimental results demonstrate that our method can improve the identification accuracy of speaker identification in noisy environments.

关键词： Speech Compressed sensing Feature extraction Noise measurement Speech recognition image reconstruction Robustness

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Trajectory matching from unsynchronized videos

Trajectory matching from unsynchronized videos

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Han Hu Jie Zhou State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology TNList Department of Automation Tsinghua University Beijing China

This paper studies the problem of spatio-temporal matching between trajectories from two videos of the same scene. In real applications, trajectories are usually extracted independently in different videos. So possibly a lot of trajectories stay “alone” (have no corresponding trajectory in the other video). In this paper, we propose a novel matching algorithm which can not only find the existing correspondences between trajectories, but also recover the corresponding trajectories of “alone” ones. First, we cast trajectory matching problem as an element recovering problem from a matrix constructed by matched trajectories of the two videos, which is naturally incomplete. Then, under affine camera assumption, we recover the matrix by sparse representation and ℓ 1 regularization techniques. Finally, the results are refined to the case of perspective projection by a local depths estimation procedure. Our algorithm can handle noisy, incomplete or outlying data. Experiments on both synthetic data and real videos show that the proposed method has good performance.

关键词： Layout Cameras Video sequences Subspace constraints Laboratories Sparse matrices Computer vision Feature extraction image reconstruction Intelligent systems

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Tomographic evaluation of a dual head PET

Tomographic evaluation of a dual head PET

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Nikos Efthimiou Spyros Maistros Xristoforos Tripolitis George Panayiotakis Alexandros Samartzis George Loudos Medical Physics Department University of Patras Patras Greece Nuclear Medicine Department Evangelismos General Hospital Athens Greece Medical Instruments Department Technological Educational Institute of Athens Athens Greece

In this article we present the performance results in tomographic mode of a low cost PET camera, dedicated for small animal imaging. The system consists of two pixelated LSO crystal arrays, two Hamamatsu H8500 PSPMTs, fast amplification electronics and an FPGA based read out system. Tomographic experiments were carried out using phantoms consisted by capillary line sources positioned on a rotated controlled motor. The opposite PET heads are static during the tomographic experiments. The parameters related to: (i) saturation as a function of head distance and acceptance angle, (ii) effect of projections number, (iii) spatial resolution as a function of heads distance, were examined. image reconstruction has been carried out with QSPECT, an opensource software developed by our group. This software is developed for 2D reconstruction of parallel projections using projection raw data obtained from coincidence images.

关键词： Magnetic heads Positron emission tomography data acquisition Biomedical imaging Field programmable gate arrays Spatial resolution Linearity Mice Instruments Educational technology

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Scanning rodents on the High Resolution Research Tomograph (HRRT) with point spread function reconstruction: A feasibility study

Scanning rodents on the High Resolution Research Tomograph (...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Stephan A. L. Blinder Katherine Dinelle Vesna Sossi Pacific Parkinsons Research Centre University of British Columbia Vancouver Canada Department of Physics and Astronomy University of British Columbia Vancouver Canada

The ECAT High Resolution Research Tomograph (HRRT) is a dedicated human brain PET camera with a 6% absolute sensitivity and a (2.3mm) 3 spatial resolution, improving to (1.8mm) 3 when point spread function (PSF) resolution recovery algorithms are used. These values are very close to those of the dedicated small animal PET camera microPET FOCUS 120 (F120). The larger axial and transaxial FoV of the HRRT compared to the F120 allows in principle for whole body imaging of several rats at the same time thus potentially reducing scanning costs and time. In this study we investigate the feasibility of using the HRRT for small animal brain studies by comparing the tissue input binding potentials (BP ND ) obtained from scans of the same rats imaged on the F120 and on the HRRT. The animal experiments are complemented by phantom studies aimed at investigating noise properties relevant to the size of typical regions of interest used in rat brain image analysis. Our investigations show that (i) without PSF modelling the BP ND obtained from HRRT data are lower than those obtained on the F120 by 28%, (ii) with PSF modelling the BP ND obtained from HRRT data are 15% higher than those obtained on the F120, (iii) the reproducibility on the HRRT is 81% when PSF modelling is not used, lower than the F120 reproducibility (92%), and decreases even further with PSF modelling to 73%. In addition Gibbs type artefacts are clearly visible when PSF modelling is used. In summary, while the resolution achieved with PSF modelling might be comparable to that obtained with the F120, the clumpy noise structure coupled with the introduction of Gibbs type artefacts in the images reconstructed with this technique currently preclude the use of the HRRT for reliable small animal brain imaging.

关键词： image reconstruction Cameras Brain models Phantoms Spatial resolution

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incomplete motion data reconstruction for character animation

Incomplete motion data reconstruction for character animatio...

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IADIS International conference Computer Graphics, Visualization, Computer Vision and image Processing 2009, CGVCVIP 2009. Part of the IADIS Multi conference on Computer Science and Information Systems, MCCSIS 2009

作者： Xiao, Zhidong Nait-Cherif, Hammadi Zhang, Jian J. National Centre for Computer Animation Media School Bournemouth University United Kingdom

ISBN: (纸本)9789728924843

This paper explores the technique that employs Principal Component Analysis (PCA) for motion synthesis and incomplete motion data reconstruction. A low dimensional space of human motion patterns are generated from a large amount motion capture data using PCA. The generated motion pattern is then applied to synthesize different scaled human character animations with a different speed by interpolation and extrapolation from existing motion patterns. According to animators' desire, we also construct incomplete motion data for a long and continuous motion sequences. This technique provides flexibility for animators to efficiently re-use existing motion capture data for character animation. © 2009 IADIS.

关键词： Motion analysis

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Non-complete Topological Analysis in image-Based 3D Building reconstruction

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5th International conference on Universal Access in Human-Computer Interaction held at the HCI International 2009

作者： Wang, Yu Zheng, Xin Beijing Normal Univ Image Proc & Pattern Recognit Lab Beijing 100875 Peoples R China

ISBN: (纸本)9783642027123

3D reconstruction from single view is a very difficult problem in Computer vision and computer graphics. Much different from method using presently, we proposed a feasible and efficient method of 3D building reconstruction method by using non-complete topological analysis in this paper, which rapidly achieves the process of recognizing architectures based one or two images. Firstly, the Outline of visible parts of architectures is extracted from image and is analyzed to get the incomplete topology of architectures. Next, the resulted topology will be divided into different primitive geometries, and these geometries are used to match models in databases finally. Experiments show that Our method has better effectiveness and feasibility.

关键词： non-complete topology analysis 3D reconstruction weighted recognition algorithm

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Performance-based assessment of reconstructed images

Performance-based assessment of reconstructed images

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conference on Medical Imaging - image Perception, Observer Performance, and Technology Assessment

作者： Hanson, Kenneth M. Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)9780819475145

During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that the quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default "classic" value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.

关键词： tomographic reconstruction assessment of image quality Rayleigh discrimination task ROC analysis human observer machine observer entropic prior ART reconstruction algorithm MEMSYS Robert Wagner

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