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IEEE Nuclear Science Symposium / Medical Imaging conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Kyme, Andre Se, Stephen Meikle, Steven Ryder, Will Popovic, Kata Fulton, Roger Univ Sydney Fac Hlth Sci Sydney NSW 2006 Australia MDA Syst Ltd Richmond Hill ON V6V 2J3 Canada

ISBN: (纸本)9781467320306;9781467320283

Motion-compensated PET of awake animals has the potential to greatly improve translational neurological investigations by enabling brain function to be studied during learning tasks and complex behaviors. Previously we have demonstrated the feasibility of performing motion-compensated brain PET on rodents, obtaining the necessary head motion data using marker-based techniques. However, markerless motion tracking would simplify animal experiments and potentially provide more accurate pose estimates over a greater range of motion. Previously we have described a markerless stereo motion tracking system and associated algorithms and validated the approach in phantoms. In this work we performed a pilot study to demonstrate motion-compensated F-18-FDG brain imaging in an awake, unrestrained rat using head pose measurements obtained from the markerless tracking system. Motion compensation clearly worked, resulting in easily identifiable structures in the head. However, it was also obvious that considerable residual error remained after correction. Post analysis of the motion estimates indicated that the residual error was the result of occasional spurious pose estimates, most likely caused by features on non-rigid parts of the head contributing to the pose estimation. Moreover, the line-of-response rebinning used for motion correction resulted in a large proportion of lost events, leading to noisy and inconsistent projection data. The latter is avoided by using a direct list mode reconstruction. In summary, markerless tracking continues to show promise for motion-compensated imaging of awake animals, but further optimization is required to match the accuracy and consistency of marker-based tracking.

关键词： brain medical image processing motion compensation motion estimation pose estimation positron emission tomography tracking

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COMPRESSED SENSING BASED image FORMATION OF SAR/ISAR data IN PRESENCE OF BASIS MISMATCH

COMPRESSED SENSING BASED IMAGE FORMATION OF SAR/ISAR DATA IN...

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IEEE International conference on image Processing

作者： A. Khwaja X. P. Zhang Department of Electrical and Computer Engineering Ryerson University Toronto ONT Canada

This paper examines compressed sensing (CS) based image formation of synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR) data for sparse scenes containing moving targets. We consider basis mismatch for the case when the basis used for reconstruction is different from the actual one in which the reconstructed data are sparse. We use orthogonal matching pursuit (OMP) algorithm for reconstruction and show using simulated data that error between original and reconstructed data increases in presence of basis mismatch. We also show that a certain level of basis mismatch in range velocity, positions and chirp rate is acceptable to achieve reasonable image formation.

关键词： image reconstruction Azimuth Synthetic aperture radar Chirp Matching pursuit algorithms Compressed sensing vectors

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Random Routing Algorithm for Rhombic-deployed Sensor Networks Based on Compressed Sensing

Random Routing Algorithm for Rhombic-deployed Sensor Network...

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International conference on Audio, Language and image Processing

作者： Rui Wang Shuai Yu Wanggen Wan Yueyue Gao Linfeng Du School of Communication and Information Engineering Shanghai University

ISBN: (纸本)9781467301732

Joint routing and compression has been the research hotspot in practical sensor networks. Compressed sensing provides a radically different view of the structure of data and a promising new approach for jointly acquiring and aggregating data from distributed data sources. Therefore, the random routing algorithm is proposed combined with compressive sensing for energy efficient data gathering in rhombic-deployed sensor networks, which satisfies the basic principles of compressed sensing, and can effective reconstruct the original signal. The performance of reconstruction on the basis of reconstruction error, energy consumption, and running time of data reconstruction is analyzed. The experiment results validate its rationality and efficiency.

关键词： Compressed sensing random routing Sensor networks Routing algorithms data reconstruction rationality Runtime Energy efficiency data sources

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Analysis of the influence of multiple scattering on the reconstruction of ultrasound tomography signals using Synthetic Aperture Focussing Technique

Analysis of the influence of multiple scattering on the reco...

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International conference on Systems, Signals and image Processing, IWSSIP

作者： M. Hardt N.v. Ruiter H. Gemmeke Karlsruhe Institute of Technology Germany

At KIT we are developing a 3D Ultrasound Computer Tomograph (USCT) for breast cancer detection. Our current reconstruction algorithm, Synthetic Aperture Focussing Technique (SAFT) assumes single scattering for the rec... 详细信息

关键词： Ultrasonic imaging image reconstruction Scattering Three dimensional displays Gratings Ultrasonic variables measurement Computational modeling

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Structural algorithm to reservoir reconstruction using passive seismic data (synthetic example)

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AIP conference Proceedings 2012年第1期1479卷 682-685页

作者： Tatyana A. Smaglichenko Igor A. volodin Andrei A. Lukyanitsa Alexander v. Smaglichenko Maria K. Sayankina Oil and Gas Research Institute Russian Academy of Science Gubkina str.3 119333 Moscow Russia Faculty of Computational Mathematics and Cybernetics M.V. Lomonosov Moscow State University Leninskie gory 1 str.52Second Teaching Building.119991 Moscow Russia Shmidt's Institute of Physics of the Earth Russian Academy of Science Bolshaya Gruzinskaya str. 10 str.1 123995 Moscow Russia

Using of passive seismic observations to detect a reservoir is a new direction of prospecting and exploration of hydrocarbons. In order to identify thin reservoir model we applied the modification of Gaussian elimination method in conditions of incomplete synthetic data. Because of the singularity of a matrix conventional method does not work. Therefore structural algorithm has been developed by analyzing the given model as a complex model. Numerical results demonstrate of its advantage compared with usual way of solution. We conclude that the gas reservoir is reconstructed by retrieving of the image of encasing shale beneath it.

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LEvEL SET ESTIMATION from COMPRESSIvE MEASUREMENTS USING BOX CONSTRAINED TOTAL vARIATION REGULARIZATION

LEVEL SET ESTIMATION FROM COMPRESSIVE MEASUREMENTS USING BOX...

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IEEE International conference on image Processing

作者： Akshay Soni Jarvis Haupt Twin Cities Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN USA

Estimating the level set of a signal from measurements is a task that arises in a variety of fields, including medical imaging, astronomy, and digital elevation mapping. Motivated by scenarios where accurate and complete measurements of the signal may not available, we examine here a simple procedure for estimating the level set of a signal from highly incomplete measurements, which may additionally be corrupted by additive noise. The proposed procedure is based on box-constrained Total variation (Tv) regularization. We demonstrate the performance of our approach, relative to existing state-of-the-art techniques for level set estimation from compressive measurements, via several simulation examples.

关键词： Level set Noise measurement Estimation Tv Extraterrestrial measurements image reconstruction Additive noise

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DECA: Recovering fields of physical quantities from incomplete sensory data

DECA: Recovering fields of physical quantities from incomple...

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IEEE Communications Society conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Liu Xiang Jun Luo Chenwei Deng Athanasios v. vasilakos Weisi Lin School of Computer Engineering Nanyang Technological University Singapore Department of Electrical and Computer Engineering National and Technical University of Athens Greece

Although wireless sensor networks (WSNs) are powerful in monitoring physical events, the data collected from a WSN are almost always incomplete if the surveyed physical event spreads over a wide area. The reason for this incompleteness is twofold: i) insufficient network coverage and ii) data aggregation for energy saving. Whereas the existing recovery schemes only tackle the second aspect, we develop Dual-lEvel Compressed Aggregation (DECA) as a novel framework to address both aspects. Specifically, DECA allows a high fidelity recovery of a widespread event, under the situations that the WSN only sparsely covers the event area and that an in-network data aggregation is applied for traffic reduction. Exploiting both the low-rank nature of real-world events and the redundancy in sensory data, DECA combines matrix completion with a fine-tuned compressed sensing technique to conduct a dual-level reconstruction process. We demonstrate that DECA can recover a widespread event with less than 5% of the data (with respect to the dimension of the event) being collected. Performance evaluation based on both synthetic and real data sets confirms the recovery fidelity and energy efficiency of our DECA framework.

关键词： Wireless sensor networks Correlation Monitoring Routing vectors image coding Eigenvalues and eigenfunctions

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Touch less gesture user interface for 3D visualization using the Kinect platform and open-source frameworks

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5th International conference on Advanced Research and Rapid Prototyping

作者： Ruppert, G. C. S. Amorim, P. H. J. Moraes, T. F. Silva, J. v. L. Renato Archer Ctr Informat Technol Campinas SP Brazil

ISBN: (纸本)9780203181416

In this work we present a natural user interface system using hand gestures to provide touchless control of 3D visualization software using the Microsoft Kinect device. Kinect is a relatively low-cost device developed by Microsoft for the gaming industry to provide controller-free gaming, but it has potential applications in many other areas, such as: data visualization, augmented reality, accessibility and robotics. Although our solution can be used with any 3D software, the present work is primarily focused in one particular application which is the visualization of 3D medical images during a surgical procedure. The operating room is a cleansed and sterilized environment and the contact of the surgeon with traditional computer interfaces (like mouse and keyboard) could lead to contamination increasing the risk of patients infection. A touchless interface is an ideal solution since it does not demand any physical contact and still can provide the necessary control features. For the visualization of 3D medical images, we used the Invesalius software that provides 3D reconstruction of medical images with features that enable the rapid prototyping of medical models and provides high-quality visualization of 3D volumes. This software is open-source, cross-platform, multi-language and is freely available. Using open-source software libraries and image processing techniques, we implemented the hands tracking and gestures recognition from the images provided by the Kinect device and enabled the surgeon to successfully navigate through the image.

关键词： data visualization

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A NOvEL LEvEL SET FRAMEWORK FOR LOD2 BUILDING MODELING

A NOVEL LEVEL SET FRAMEWORK FOR LOD2 BUILDING MODELING

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IEEE International conference on image Processing

作者： Bing Jia Ye Zhang Yushi Chen Zhilu Wu School of Electronics and Information Technology Harbin Institute of Technology China

3D city models typically consist of thousands of buildings in different types. We usually reconstruct these buildings automatically from high-resolution satellite or airborne imagery. However, for detailed roof reconstruction, 2D information offered by imagery data is not enough while DSM data is necessary. In this paper, we propose a novel level set framework for 3D building models in LOD2 with geometry structure of typical roofs. Local information is introduced towards multiphase and multichannel level set method. Its energy function is minimized when each part of roof data corresponds to the same normal vector as feature values for level set segmentation. The advantage of this method is that for complex building models, roof primitives as well as roof topology graph can be extracted from high-resolution DSM data with high accuracy, evaluated by completeness of segmentation and RMSE of 3D reconstruction. Thus, LOD2 building models can be reconstructed automatically with good performance. The very promising experimental results demonstrate the potentials of our method for large-scale building reconstruction in LOD2.

关键词： Buildings Level set Solid modeling image reconstruction Atmospheric modeling image segmentation vectors

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PARTIALLY PARALLEL MR image reconstruction USING SENSITIvITY ENCODING

PARTIALLY PARALLEL MR IMAGE RECONSTRUCTION USING SENSITIVITY...

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IEEE International conference on image Processing

作者： Maryam Yashtini William W. Hager Yunmei Chen Xiaojing Ye Department of Mathematics University of Florida Gainesville FL USA Department of Mathematics Georgia Institute of Technology Atlanta GA USA

A new algorithm is presented for efficiently solving image reconstruction problems that arise in partially parallel magnetic resonance imaging. This algorithm minimizes an objective function of the form φ(Bu) + 1/2‖F_pSu - f‖~2, where φ is the regularization term which may be nonsmooth. In image reconstruction, the φ term corresponds to total variation smoothing and/or L1 regularization term. The least square term 1/2‖F_pSu - f‖~2 is the fidelity term. In our application, f represents undersampled data from a partially parallel imaging (PPI) system. The proposed algorithm is a generalization of the Bregman operator splitting algorithm with variable stepsize (BOSvS) in which the previous Barzilai-Borwein (BB) step is replaced by a cyclic BB (CBB) step, and an L1 term Ψ is added to the energy function. Experimental results on clinical partially parallel imaging data are given.

关键词： image reconstruction Sensitivity Indexes Hyperspectral imaging Algorithm design and analysis Magnetic resonance imaging

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