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Efficient MR image reconstruction for compressed MR imaging

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

作者： Huang, Junzhou Zhang, Shaoting Metaxas, Dimitris Dept Comp Sci Piscataway NJ 08854 USA

ISBN: (纸本)3642157041

In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (Tv) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and Tv norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. (C) 2011 Elsevier B.v. All rights reserved.

关键词： Convex optimization Compressive sensing MR image reconstruction

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Performance Evaluation of reconstruction with Fan-Beam Algorithm with no Backprojection Weight in Truncated Projection Completion using Linear Prediction

Performance Evaluation of Reconstruction with Fan-Beam Algor...

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IEEE Region 10 conference on TENCON

作者： Sumith, K. Narasimhadhan, A. v. Rajgopal, Kasi Indian Inst Sci Dept Elect Engg Bangalore 560012 Karnataka India

ISBN: (纸本)9781457702556

The work presented in this paper examines the performance of reconstruction from truncated projections using linear prediction for projection completion and recently proposed fan beam algorithm having no backprojection weight. The truncation in the tomographic projections can occur due to compact nature of the detector, outsized imaging object and region of interest (ROI) reconstruction applications. The reconstruction of the object function from truncated projections suffers from undesirable truncation artifacts and incorrect reconstructed density values. In this work, the truncated projection data is estimated by using the linear projection technique. The object is then reconstructed from the completed projections by using Hilbert filter based fan-beam algorithm with no backprojection weight. The resulting reconstruction improves the image quality in terms of noise performance characteristics. Simulation results are presented to show the improvements in image quality and compared with the reconstruction obtained using ramp filtered fan-beam algorithm.

关键词： Fan-beam algorithm truncation Linear prediction

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Exact, scaled image rotations in finite Radon transform space

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PATTERN RECOGNITION LETTERS 2011年第9期32卷 1415-1420页

作者： Svalbe, Imants Monash Univ Sch Phys Clayton Vic 3800 Australia

The Finite Radon Transform (FRT) is a discrete analogue of classical tomography. The FRT permits exact reconstruction of a discrete object from its discrete projections. The set of projection angles for the FRT is intrinsic to each image array size. It is shown here that the set of FRT angles is closed under a rotation by any of its members. A periodic re-ordering of the elements of the 10 FRT projections is then equivalent to an exact 2D image rotation. FRT-based rotations require minimal interpolation and preserve all of the original image pixel intensities. This approach has applications in image feature matching, multi-scale data representation and data encryption. (C) 2010 Elsevier B.v. All rights reserved.

关键词： Discrete Radon projection image rotation Affine transforms

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Effects of Attenuation in Single Slow Rotation Dynamic SPECT

Effects of Attenuation in Single Slow Rotation Dynamic SPECT

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IEEE Nuclear Science Symposium/Medical Imaging conference (NSS/MIC)/18th International Workshop on Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors

作者： Humphries, Thomas Celler, Anna Trummer, Manfred Simon Fraser Univ Dept Math Burnaby BC V5A 1S6 Canada Univ British Columbia Dept Radiol Vancouver BC V5Z 1L3 Canada

ISBN: (纸本)9781467301206

The goal of single slow rotation dynamic SPECT is to reconstruct a dynamic image from data acquired with a single slow rotation of the camera. In this approach, the distribution of activity is assumed to change with every stop made by the camera, and all time frames of the 4D image are simultaneously reconstructed, using a temporal constraint to link them together. The dSPECT algorithm, for instance (Farncombe et al., 2001), restricts the behaviour of the time activity curve (TAC) in every voxel of the image, requiring it either strictly increase, strictly decrease, or increase to a maximum and then decrease. Attenuation correction (AC) is critical to this approach, in order to separate the effects of attenuation on projection data from the actual tracer kinetics. Here we present new analysis indicating that modeling attenuation in the system matrix, although sufficient for AC in conventional (static) SPECT imaging, does not properly account for attenuation effects when reconstructing a dynamic image from data acquired with a single slow rotation. Noticeable artifacts occur in TACs extracted from the reconstructed image as a result. These artifacts correspond to periods of the acquisition where the amount of attenuating material between the camera and dynamic regions changes significantly. We investigate a post-reconstruction approach to correct for these artifacts, in which a template approximating the dynamic image is created, analytically projected, and then reconstructed. This procedure provides an indication of the nature of the artifacts present in the original reconstructed image, allowing for a correction to be applied. An experiment using a digital phantom and the dSPECT reconstruction algorithm indicates that this approach noticeably reduces most attenuation artifacts, although some still persist. Thus, the acquisition protocol in any single slow rotation dynamic SPECT study must be carefully chosen to minimize errors related to attenuation.

关键词： Analytical models Equations Mathematical model

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A New Method for Classification of Events in Noisy Hydrophone data

A New Method for Classification of Events in Noisy Hydrophon...

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IEEE Pacific Rim conference on Communications, Computers and Signal Processing (PACRIM)

作者： Sattar, F. Driessen, P. F. Tzanetakis, G. Page, W. H. Univ Victoria NEPTUNE Canada Victoria BC V8W 2Y2 Canada Victoria Univ Dept Elect & Comp Engn Victoria BC Canada Victoria Univ Dept Comp Sci Victoria BC Canada Massey Univ Inst Food Nutr & Human Hlth Palmerston North New Zealand

ISBN: (纸本)9781457702518

In this paper a new method for classifying events in noisy hydrophone data is developed. The method takes an image processing approach to the 1D hydrophone data by first converting it into a log-frequency spectrogram image (cepstrum). This image is then filtered by reconstructing it based on mutual information (MI) criteria of the dominant orientation map. The features of the reconstructed cepstrum are then enhanced using a combination of edge-tracking and noise smoothing. Feature classification on the processed cepstrum is performed using a least-squares support vector machine (LS-SvM). The method showed event detection sensitivity in excess of 99% for rare events such as whale calls from noisy hydrophone recordings from the NEPTUNE Canada project, with in excess of 97% specificity and 98% overall accuracy. With relatively low computational cost and high accuracy, the proposed method is useful for automated long-term monitoring of a wide variety of marine mammals and human related activities from hydrophone data.

关键词： Cepstrum Feature extraction NEPTUNE Canada project Noise Sonar equipment Spectrogram Time frequency analysis Wavelet transforms cepstrum dominant orientation map edge tracking event classification feature classification feature extraction geophysical image processing hydrophones image classification image filtering image processing image reconstruction image reconstruction least-squares support vector machine log-frequency spectrogram image mutual information criteria noise smoothing noisy hydrophone data oceanographic techniques smoothing methods support vector machines

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Projective reconstruction from incomplete trajectories by global and local constraints

Projective reconstruction from incomplete trajectories by gl...

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8th European conference on visual Media Production, CvMP 2011

作者： Ackermann, H. Rosenhahn, B. Leibniz University Hanover Germany

ISBN: (纸本)9780769546216

The paper deals with projective shape and motion reconstruction by subspace iterations. A prerequisite of factorization-style algorithms is that all feature points need be observed in all images, a condition which is hardly realistic in real videos. We therefore address the problem of estimating structure and motion considering missing features. The proposed algorithm does not require initialization and uniformly handles all available data. The computed solution is global in the sense that it does not merge partial solutions incrementally or hierarchically. The global cost due to the factorization is further amended by local constraints to regularize and stabilize the estimations. It is shown how both costs can be jointly minimized in the presence of unobserved points. By synthetic and real image sequences with up to 60% missing data we demonstrate that our algorithm is accurate and reliable. © 2011 IEEE.

关键词： Factorization

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An analysis of recovering three-dimensional points from image correspondences using surface curvature

An analysis of recovering three-dimensional points from imag...

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2011 International conference on Machine Learning and Cybernetics, ICMLC 2011

作者： Teng, Chin-Hung Department of Information Communication YuanZe University Chung-Li 32003 Taiwan

ISBN: (纸本)9781457703065

This paper presents a method for recovering 3D points from image correspondences using surface characteristics such as mean and Gaussian curvatures. We first give an analysis about how to estimate the mean and Gaussian curvatures from a set of 3D points, and then incorporate the curvature estimation scheme into the reconstruction of 3D points where an optimization process is formulated with the surface curvatures modeled as soft constraints. To analyze the performance of proposed 3D reconstruction method, some simulated data, including the points on surfaces of a plane, a cylinder and a sphere, is generated to test this approach. The experimental results demonstrated that the surface curvature can indeed improve the accuracy of 3D point reconstruction. Some real image data is also tested and the results also support this point. © 2011 IEEE.

关键词： Curve fitting

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A New image-Based Method for Event Detection and Extraction of Noisy Hydrophone data

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8th International conference on image Analysis and Recognition (ICIAR) / 2nd International conference on Autonomous and Intelligent Systems (AIS)

作者： Sattar, F. Driessen, P. F. Tzanetakis, G. Univ Victoria NEPTUNE Canada Victoria BC Canada Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 2Y2 Canada Univ Victoria Dept Comp Sci Victoria BC V8W 2Y2 Canada

ISBN: (纸本)9783642215957;9783642215964

In this paper, a new image based method for detecting and extracting events in noisy hydrophone data sequence is developed. The method relies on dominant orientation and its robust reconstruction based on mutual information (MI) measure. This new reconstructed dominant orientation map of the spectrogram image can provide key segments corresponding to various acoustic events and is robust to noise. The proposed method is useful for long-term monitoring and a proper interpretation for a wide variety of marine mammals and human related activities using hydrophone data. The experimental results demonstrate that this image based approach can efficiently detect and extract unusual events, such as whale calls from the highly noisy hydrophone recordings.

关键词： Event detection/extraction Noisy hydrophone data Dominant orientation map Long-term monitoring Bioacoustics Marine mammals

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PET motion correction in LOR space using scanner-independent, adaptive projection data for image reconstruction with PRESTO

PET motion correction in LOR space using scanner-independent...

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2011 IEEE Nuclear Science Symposium and Medical Imaging conference, NSS/MIC 2011

作者： Scheins, J.J. Ullisch, M. Tellmann, L. Weirich, Ch. Rota Kops, E. Herzog, H. Shah, N.J. Institute of Neuroscience and Medicine Forschungszentrum Jülich GmbH Germany

ISBN: (纸本)9781467301183

Figure 2 shows reconstructed images of a two-chamber phantom (filled with two activity concentrations) which was measured in 7 different positions. The applied motion of the phantom induces a significant image degradation (left). Motion parameters were extracted from EPI volumes to correct the emission data before the reconstruction with PRESTO. The blurring due to motion completely vanishes (right).

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image decoding optimization based on compressive sensing

Image decoding optimization based on compressive sensing

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7th International conference on Scientific Computing and Applications

作者： Zhang, Zhen Shi, Yunhui Kong, Dehui Ding, Wenpeng Yin, Baocai Beijing Univ Technol Coll Comp Sci & Technol Beijing Municipal Key Lab Multimedia & Intelligen Beijing 100124 Peoples R China

Transform-based image codec follows the basic principle: the reconstructed quality is decided by the quantization level. Compressive sensing (CS) breaks the limit and states that sparse signals can be perfectly recovered from incomplete or even corrupted information by solving convex optimization. Under the same acquisition of images, if images are represented sparsely enough, they can be reconstructed more accurately by CS recovery than inverse transform. So, in this paper, we utilize a modified Tv operator to enhance image sparse representation and reconstruction accuracy, and we acquire image information from transform coefficients corrupted by quantization noise. We can reconstruct the images by CS recovery instead of inverse transform. A CS-based JPEG decoding scheme is obtained and experimental results demonstrate that the proposed methods significantly improve the PSNR and visual quality of reconstructed images compared with original JPEG decoder. (C) 2011 Elsevier B.v. All rights reserved.

关键词： Compressive sensing image decoding Total variation SOCP

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