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IEEE International Symposium on Biomedical Imaging

作者： Yanjie Zhu Yin Wu Yuanjie Zheng Ed X. Wu Leslie Ying Dong Liang Paul C. Lauterbur Research Centre for Biomedical Imaging Shenzhen Institutes of Advanced Technology Key Laboratory of Health Informatics Chinese Academy of Sciences Shenzhen China Department of Radiology University of Pennsylvania PA USA Laboratory of Biomedical Imaging and Signal Processing Department of Electrical and Electronic Engineering University of Hong Kong Pokfulam Hong Kong China Department of Electrical Engineering and Computer Science University of Wisconsin Milwaukee Milwaukee WI USA

Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.

关键词： Tensile stress Diffusion tensor imaging Image reconstruction Joints Compressed sensing Biological system modeling

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Impaired Resting State Networks in Temporal Lobe Epilepsy: A Resting State fMRI Study

Impaired Resting State Networks in Temporal Lobe Epilepsy: A...

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Iranian Conference of Biomedical engineering

作者： Marzie Fereidouni Hamid Soltanian-Zadeh Quan Jiang Kost V. Elisevich Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran NMR Laboratory Department of Neurology Henry Ford Hospital Detroit Michigan USA epartment of Clinical Neurosciences Spectrum Health System Grand Rapids Michigan USA

ISBN: (纸本)9781467331289

Temporal lobe epilepsy (TLE) is the most common type of human refractory epilepsy and can cause widespread impairments in brain functionality. Previous studies show functional and structural abnormalities in different regions of TLE patients' brain in comparison with normal subjects. However, limited studies have been done on connectivity abnormalities of resting state networks (RSN) in TLE patients and most of them studied default mode network (DMN) only. In this paper, nine independent spatial maps of the brain were identified by applying independent component analysis (ICA) on functional magnetic resonance images (fMRI) of the subjects. These maps were classified into four resting state networks: visual network, auditory network, default mode network, and attention network (including right and left fronto-parietal networks and core network). Functional connectivity between time courses of the nine components were computed and then compared between TLE patients and healthy subjects. Results show that there are significant between-group differences in functional connectivity among different brain networks including decrease in functional connections of visual cortex with two other networks, DMN and attention network, and decrease in functional connectivity between DMN and left fronto-parietal network. An increase in functional connectivity between DMN and core network and also between right fronto-parietal network and auditory network is observed.

关键词： Temporal lobe epilepsy Functional connectivity Resting state networks

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Voxel-based treatment prediction of glioblastoma multiform tumor using diffusion tensor imaging

Voxel-based treatment prediction of glioblastoma multiform t...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

This paper proposes a method to predict the effect of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The prediction is critical for effective treatment planning. The proposed method is developed and evaluated using Diffusion Tensor Imaging (DTI) and post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI) of 14 patients with GBM tumors gathered before and after the treatment. First, the proposed method calculates diffusion anisotropy indices (DAI) of all voxels in the brain. These diffusion anisotropy indices are Fractional Anisotropy (FA), Mean Diffusivity (MD), Relative Anisotropy (RA), and Volume Ratio (VR). Then, it registers post-treatment pc-T1-MRI and pre-treatment DAI maps to pre-treatment pc-T1-MRI. Next, it uses a thresholding method to segment the tumor from pc-T1-MRI studies. Comparing Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI, the DAIs of the tumor are labeled based on their response to the treatment. The voxels of 7 patients are randomly selected to train 4 classifiers (ANN, SVM, KNN, and ANFIS) and then all voxels of the other 7 patients are used to test them. For each classifier, four performance measures (sensitivity, specificity, positive predictive value, and accuracy) are calculated. Experimental results show that the ANFIS is more accurate than the other classifiers in predicting the treatment response.

关键词： Support vector machines Noise Magnetic resonance imaging Sensitivity Tumors Biomedical imaging Artificial neural networks

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Implementing real-time partitioned convolution algorithms on conventional operating systems

Implementing real-time partitioned convolution algorithms on...

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14th International Conference on Digital Audio Effects, DAFx 2011

作者： Battenberg, Eric Avižienis, Rimas Parallel Computing Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley CA United States

ISBN: (纸本)9782954035109

We describe techniques for implementing real-time partitioned convolution algorithms on conventional operating systems using two different scheduling paradigms: time-distributed (cooperative) and multi-threaded (preemptive). We discuss the optimizations applied to both implementations and present measurements of their performance for a range of impulse response lengths on a recent high-end desktop machine. We find that while the time-distributed implementation is better suited for use as a plugin within a host audio application, the preemptive version was easier to implement and significantly outperforms the time-distributed version despite the overhead of frequent context switches.

关键词： Impulse response

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Automatic organs' detection in WCE

Automatic organs' detection in WCE

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International Symposium on Artificial Intelligence and Signal processing (AISP)

作者： Omid Haji-Maghsoudi Alireza Talebpour Hamid Soltanian-Zadeh Navid Haji-maghsoodi Department of Radiation Medicine Shahid Beheshti University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Hospital Detroit MI USA Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Mechatronics Sharif University of Tehran Tehran Iran

Wireless capsule endoscopy (WCE) views the entire gastrointestinal (GI) tract. A main problem associated with this novel device is that too many frames must be reviewed by physicians. Thus it is essential to find an automatic and intelligent method to help physicians. One of the problems in WCE is its difficulty to distinguish among different organ's tissues. So, we introduce two novel algorithms which are able to classify main organs (among esophagus, stomach, small bowel and colon) in WCE's frames. In order to obtain our aim, we use statistic features (Haralick features) and non-statistic features (different diagrams and Gabor filter banks), colored features and non-colored features. Our experimental studies indicate good results that are shown in conclusion.

关键词： Level set Medical services Gabor filters Active contours Wireless communication Optical wavelength conversion Esophagus

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A flexible modified dipole antenna printed on PET film

A flexible modified dipole antenna printed on PET film

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Lei Wang Yong-Xin Guo Budiman Salam Chee Wai Albert Lu Millimeter Wave Technique Laboratory Nanjing University of Science and Technology of PLA Nanjing China Millimeter Wave Technique Laboratory Nanjing University of Science and Technology Nanjing China Department of Electrical and Computer Engineering National University of Singapore Singapore Large Area Processing Programme Singapore Institute of Manufacturing Technology Singapore Singapore Institute of Manufacturing Technology Singapore SG

A flexible transparent modify dipole antenna printed on PET film is presented in this paper. The proposed antenna was designed to operate at 2.4GHz for ISM applications. The impedance characteristic and the radiation characteristic were simulated and measured. The proposed antenna has good performance. It can be easily mounted on conformal shape, because it is fabricated on PET film having the flexible characteristic.

关键词： Dipole antennas Antenna measurements Positron emission tomography Ultra wideband antennas Films

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Erratum (“A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals” Neural Computation, Volume 18, Number 10, pp. 2465–2494)

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Neural Computation 2012年第4期24卷 1106-1107页

作者： Iahn Cajigas Lakshminarayan Srinivasan Neuroscience Statistics Research Laboratory Department of Anesthesia and Critical Care Massachusetts General Hospital Charlestown MA 02129 U.S.A. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 U.S.A. and Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge MA 02139 U.S.A. Neural Signal Processing Laboratory Department of Radiology David Geffen School of Medicine University of California Los Angeles CA 90095 U.S.A.

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Elastic shape registration using an incremental free form deformation approach with the ICP algorithm

Elastic shape registration using an incremental free form de...

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Canadian Conference on computer and Robot Vision

作者： Abdelmunim, Hossam Farag, Aly A. Computer and Systems Engineering Department Faculty of Engineering Ain Shams University Cairo 11517 Egypt Computer Vision and Image Processing Laboratory Electrical and Computer Engineering Department University of Louisville KY 40292 United States

ISBN: (纸本)9780769543628

Shape registration is one of the most challenging problems in computer vision and medical imaging. The process is affected by the way the shape is represented and the form of transformation used to move the source shape. Our paper handles the elastic shape registration by combining the incremental free form deformation (IFFD) with the point-based registration technique using the sum of least squares method. The iterative closest point (ICP) algorithm is used as a criteria to establish point correspondences in each level of the IFFD framework. The free form deformation (FFD) is well known in the literature and works by forming a lattice of control points that can move and hence deform the domain grid points smoothly and uniformly under some shape constrains. The control lattice resolution is increased step by step to achieve a satisfactory deformation of the source shape to exactly match the target boundaries. Our point-based registration is based on least squares that measure the Euclidean distance between source and target boundaries in addition to the shape constrains. The minimization gives a closed form solution of the lattice control points positions. Promising results will be demonstrated for closed and open shapes and structures. The approach can also work for structures that contain multiple parts without any problems. © 2011 IEEE.

关键词： Medical imaging

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7191 LNCS卷 V-VII页

作者： Cichocki, Andrzej Theis, Fabian Yeredor, Arie Zibulevsky, Michael Helmholtz Center Munich Institute of Bioinformatics and Systems Biology Ingolstädter Landstr. 1 85764 Neuherberg Germany Riken Brain Science Institute Laboratory for Advanced Brain Signal Processing 2-1 Hirosawa Wako-shi 351-0198 Saitama Japan Tel-Aviv University School of Electrical Engineering Tel-Aviv 69978 Israel Technion - Israel Institute of Technology Department of Computer Science Haifa 32000 Israel

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Accelerating geospatial analysis on GPUs using CUDA

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Journal of Zhejiang University-Science C(computers and Electronics) 2011年第12期12卷 990-999页

作者： Ying-jie XIA Li KUANG Xiu-mei LI Hangzhou Institute of Service Engineering Hangzhou Normal University Hangzhou 310012 China Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Provincial Key Laboratory for Computer Information Processing Technology Sooehow University Soochow 215006 China

Inverse distance weighting (IDW) interpolation and viewshed are two popular algorithms for geospatial *** interpolation assigns geographical values to unknown spatial points using values from a usually scattered set of known points,and viewshed identifies the cells in a spatial raster that can be seen by *** the implementations of both algorithms are available for different scales of input data,the computation for a large-scale domain requires a mass amount of cycles,which limits their *** to the growing popularity of the graphics processing unit (GPU) for general purpose applications,we aim to accelerate geospatial analysis via a GPU based parallel computing *** this paper,we propose a generic methodological framework for geospatial analysis based on GPU and its programming model Compute Unified Device Architecture (CUDA),and explore how to map the inherent parallelism degrees of IDW interpolation and viewshed to the framework,which gives rise to a high computational *** CUDA-based implementations of IDW interpolation and viewshed indicate that the architecture of GPU is suitable for parallelizing the algorithms of geospatial *** results show that the CUDA-based implementations running on GPU can lead to dataset dependent speedups in the range of 13-33-fold for IDW interpolation and 28-925-fold for viewshed *** computation time can be reduced by an order of magnitude compared to classical sequential versions,without losing the accuracy of interpolation and visibility judgment.

关键词： General purpose GPU CUDA Geospatial analysis parallelization

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