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检索条件"任意字段=Parallel and Distributed Methods for Image Processing"

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image Classification Optimization of High Resolution Tissue images

Image Classification Optimization of High Resolution Tissue ...

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9th International Conference on Large-Scale Scientific Computations (LSSC)

作者： Kozlovszky, M. Hegedus, K. Windisch, G. Kovacs, L. Pinter, G. Obuda Univ John von Neumann Fac Informat Budapest Hungary

ISBN: (纸本)9783662438800;9783662438794

Generic image classification methods are not performing well on tissue images. Such software solutions are producing high number of false negative and positive results, which prevents their clinical usage. We have created the MorphCeck high resolution tissue image processing framework, which enables us to collect morphological and morphometrical parameter values of the examined tissues. Size of such tissue images can easily reach the order of 100 MB-1 GB. Therefore, the image processing speed and effectiveness is an important factor. Our main goal is to accurately evaluate high resolution H-E (hematoxilin-eozin) stained colon tissue sample images, and based on the parameters classify the images into differentiated sets according to the structure and the surface manifestation of the tissues. We have interfaced our MorphCheck tissue image measurement software framework with the WND-CHARM general purpose image classifier and tried to classify high resolution tissue images with this combined software solution. The classification is by default initiated with a large training set and three main classes (healthy, adenoma, carcinoma), however the new image classification process' wall-clock time was intolerably high on single core PC. The processing time is depending on the size/resolution of the image and the size of the training set. Due to the tissue specific image parameters the classification effectiveness was promising. So we have started a development process to decrease the processing time and further increase the accuracy of the classification. We have developed a workflow based parallel version of the MorphCheck and WND-CHARM classifier software. In collaboration with the MTA SZTAKI Application Porting Centre the WND-CHARM has been ported to some distributed computing infrastructure (DCI). The paper introduces the steps that were taken to optimize WND-CHARM applications running faster using DCIs and some performance results of the tissue image classification proce

关键词： Application porting Medical image processing workflow HP-SEE gUSE Scalability MorphCheck WND-CHARM

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parallel Computing of Particle Filtering Algorithms for Target Tracking Applications

Parallel Computing of Particle Filtering Algorithms for Targ...

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作者： Wu, Jiande University of New Orleans

学位级别：Ph.D.

Particle filtering has been a very popular method to solve nonlinear/non-Gaussian state estimation problems for more than twenty years. Particle filters (PFs) have found lots of applications in areas that include nonlinear filtering of noisy signals and data, especially in target tracking. However, implementation of high dimensional PFs in real-time for large-scale problems is a very challenging computational task. parallel & distributed (P&D) computing is a promising way to deal with the computational challenges of PF methods. The main goal of this dissertation is to develop, implement and evaluate computationally efficient PF algorithms for target tracking, and thereby bring them closer to practical applications. To reach this goal, a number of parallel PF algorithms is designed and implemented using different parallel hardware architectures such as Computer Cluster, Graphics processing Unit (GPU), and Field-Programmable Gate Array (FPGA). Proposed is an improved PF implementation for computer cluster - the Particle Transfer Algorithm (PTA), which takes advantage of the cluster architecture and outperforms significantly existing algorithms. Also, a novel GPU PF algorithm implementation is designed which is highly efficient for GPU architectures. The proposed algorithm implementations on different parallel computing environments are applied and tested for target tracking problems, such as space object tracking, ground multitarget tracking using image sensor, UAV-multisensor tracking. Comprehensive performance evaluation and comparison of the algorithms for both tracking and computational capabilities is performed. It is demonstrated by the obtained simulation results that the proposed implementations help greatly overcome the computational issues of particle filtering for realistic practical problems.

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5th International Conference in image processing and Communications, IP&C 2013

5th International Conference in Image Processing and Communi...

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5th International Conference in image processing and Communications, IP&C 2013

ISBN: (纸本)9783319016214

The proceedings contain 52 papers. The special focus in this conference is on image processing and Communications. The topics include: Adaptive windowed threshold for box counting algorithm in cytoscreening applications;corneal endothelial grid structure factor based on coefficient of variation of the cell sides lengths;a distributed approach for development of deformable model-based segmentation methods;enhancement of low-dose CT brain scans using graph-based anisotropic interpolation;using of EM algorithm to image reconstruction problem with tomography noises;the perception of humanoid robot by human;a fast histogram estimation based on the Monte Carlo method for image binarization;adaptation of the combined image similarity index for video sequences;time-frequency analysis of image based on stockwell transform;2DKLT-based color image watermarking;knowledge transformations applied in image classification task;problems of infrared and visible-light images automatic registration;semantics driven table understanding in born-digital documents;contextual possibilistic knowledge diffusion for images classification;image feature extraction using compressive sensing;a modification of the parallel spline interpolation algorithms;local Eigen background substraction;polarization imaging in 3D shape reconstrucion;layer image components geometry optimization;extraction of data from limnigraf chart images;a simplified visual cortex model for efficient image codding and object recognition;fuzzy rule-based systems for optimizing power consumption in data centers;an algorithm for finding shortest path tree using ant colony optimization metaheuristic and a sensor network gateway for IP network and SQL database.

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parallel implementation of a X-ray tomography reconstruction algorithm for high-resolution studies

Parallel implementation of a X-ray tomography reconstruction...

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13th Mediterranean Conference on Medical and Biological Engineering and Computing 2013, MEDICON 2013

作者： Garcia, J. Abella, M. de Molina, C. Liria, E. Isaila, F. Carretero, J. Desco, M. Computer Architecture and Communication Area University Carlos III Madrid Spain Bioengineering and Aerospace Engineering Dept. University Carlos III Madrid Spain Madrid Spain Madrid Spain

ISBN: (纸本)9783319008455

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flatpanel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speed-up the reconstruction of CT data in order to extend its clinical applications. The evolution of the semiconductor detector panels has resulted in an increase of detector elements density, which produces a higher amount of data to process. This work focuses on both standard and future high-resolution studies, in which multiple level of parallelism will be needed in the reconstruction process. In addition, this paper addresses the future challenges of processing high-resolution images in many-core and distributed architectures. © Springer International Publishing Switzerland 2014.

关键词： parallel architectures

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A Rapid Fluorescence Lifetime image Acquistion Method Based on Time-gated Fluorescence Lifetime Imaging Microscopy 2

A Rapid Fluorescence Lifetime Image Acquistion Method Based ...

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2nd International Conference on Systems and Informatics (ICSAI)

作者： Liu, Yang Zhou, Yan Liu, Yuliang Chinese Acad Sci Inst Semicond Optoelect Syst Lab Beijing Peoples R China

ISBN: (纸本)9781479954582

Besides the regular biological or biomedical imaging applications, time-gated fluorescence lifetime imaging microscopy (FLIM) could be used to image living cells or rapid biochemistry reactions by its advantage of wide field and obvious parallel acquisition speed. As the basis of system detection mode, a good fitting algorithm could satisfy the lifetime precision and acquisition demand at the same time. The common used fluorescence lifetime fitting methods include rapid fluorescence lifetime determination(RLD), linear least square method (LLS) and iterative nonlinear least square (NLLS) method. In this study, we compared these three methods and analyzed the lifetime results. It demonstrated the RLD algorithm could achieve a fast processing speed and a good contrast of lifetime map, however, it shows the results of the rapid fitted lifetime map exists some distributed noise caused by insufficient time-resolved fluorescence intensity images. To remove these noise spots and preserve the lifetime map precision, we chose a four-order partial differential equations (PDEs), which achieved a trade-off between noise-removing and lifetime map feature. In this paper, we proposed a rapid fluorescence lifetime acquisition method combining rapid lifetime determination and four-order PDEs algorithm based on time-gated FLIM, which could satisfy the high speed detection and lifetime precision demand of living cells or rapid biochemical reactions.

关键词： time-gated FLIM rapid fitting method noise removal fourth -order PDE nonlinear diffusion

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Generalizations of the Alternating Direction Method of Multipliers for Large-Scale and distributed Optimization

Generalizations of the Alternating Direction Method of Multi...

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作者： Deng, Wei Rice University

学位级别：Ph.D.

Due to the dramatically increasing demand for dealing with "Big Data", efficient and scalable computational methods are highly desirable to cope with the size of the data. The alternating direction method of multipliers (ADMM), as a versatile algorithmic tool, has proven to be very effective at solving many large-scale and structured optimization problems, particularly arising from the areas of compressive sensing, signal and image processing, machine learning and applied statistics. Moreover, the algorithm can be implemented in a fully parallel and distributed manner to process huge datasets. These benefits have mainly contributed to the recent renaissance of ADMM for modern applications. This thesis makes important generalizations to ADMM to improve its flexibility and efficiency, as well as extending its convergence theory. Firstly, we allow more options of solving the subproblems either exactly or approximately, such as linearizing the subproblems, taking one gradient descent step, and approximating the Hessian. Often, when subproblems are expensive to solve exactly, it is much cheaper to compute approximate solutions to the subproblems which are still good enough to guarantee convergence. Although it may take more iterations to converge due to less accurate subproblems, the entire algorithm runs faster since each iteration takes much less time. Secondly, we establish the global convergence of these generalizations of ADMM. We further show the linear convergence rate under a variety of scenarios, which cover a wide range of applications in practice. Among these scenarios, we require that at least one of the two objective functions is strictly convex and has Lipschitz continuous gradient, along with certain full rank conditions on the constraint coefficient matrices. The derived rate of convergence also provides some theoretical guidance for optimizing the parameters of the algorithm. In addition, we introduce a simple technique to improve an existing convergence

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Approximate Maximum Common Sub-graph Isomorphism Based on Discrete-Time Quantum Walk 22

Approximate Maximum Common Sub-graph Isomorphism Based on Di...

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22nd International Conference on Pattern Recognition (ICPR)

作者： Lu, Kai Zhang, Yi Xu, Kai Gao, Yinghui Wilson, Richard Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha Hunan Peoples R China Natl Univ Def Technol Coll Comp Changsha Hunan Peoples R China Natl Univ Def Technol Coll Elect Sci & Engn Changsha Hunan Peoples R China Univ York Dept Comp Sci York YO10 5GH N Yorkshire England

ISBN: (纸本)9781479952083

Maximum common sub-graph isomorphism (MCS) is a famous NP-hard problem in graph processing. The problem has found application in many areas where the similarity of graphs is important, for example in scene matching, video indexing, chemical similarity and shape analysis. In this paper, a novel algorithm Qwalk is proposed for approximate MCS, utilizing the discrete-time quantum walk. Based on the new observation that isomorphic neighborhood group matches can be detected quickly and conveniently by the destructive interference of a quantum walk, the new algorithm locates an approximate solution via merging neighborhood groups. Experiments show that Qwalk has better accuracy, universality and robustness compared with the state-of-the-art approximate MCS methods. Meanwhile, Qwalk is a general algorithm to solve the MCS problem approximately while having modest time complexity.

关键词： discrete-time quantum walk maximum common sub-graph quantum interference

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Combination feature for image retrieval in the distributed datacenter

Combination feature for image retrieval in the distributed d...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Di Yang Jianxin Liao Qi Qi Jingyu Wang Haifeng Sun Shan Jiang State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781479976164

Since the emergence of cloud datacenters provides an enormous amount of resources easily accessible to people, it is challenging to provide an efficient search framework in such a distributed environment. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These methods are insufficient to meet requirements of content based image retrieval (CBIR) and more powerful search frameworks are needed. In this paper, we present LCFIR, an effective image retrieval framework for fast content location in the distributed situation. It adopts the peer-to-peer paradigm and combines color and edge features. The basic idea is to construct multiple replicas of an image's index through exploiting the property of Locality Sensitive Hashing (LSH). Thus, the indexes of similar images are probabilistically gathered into the same node without the knowledge of any global information. The empirical results show that the system is able to yield high accuracy with load balancing, and only contacts a few number of the participating nodes.

关键词： Indexes Peer-to-peer computing image retrieval image color analysis Feature extraction Query processing image edge detection

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Complex Network Analysis Using parallel Approximate Motif Counting

Complex Network Analysis Using Parallel Approximate Motif Co...

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International Symposium on parallel and distributed processing (IPDPS)

作者： George M. Slota Kamesh Madduri Department of Computer Science and Engineering The Pennsylvania State University University Park PA USA

Subgraph counting forms the basis of many complex network analysis metrics, including motif and anti-motif finding, relative graph let frequency distance, and graph let degree distribution agreements. Determining exact subgraph counts is computationally very expensive. In recent work, we present FASCIA, a shared-memory parallel algorithm and implementation for approximate subgraph counting. FASCIA uses a dynamic programming-based approach and is significantly faster than exhaustive enumeration, while generating high-quality approximations of subgraph counts. However, the memory usage of the dynamic programming step prohibits us from applying FASCIA to very large graphs. In this paper, we introduce a distributed-memory parallelization of FASCIA by partitioning the graph and the dynamic programming table. We discuss a new collective communication scheme to make the dynamic programming step memory-efficient. These optimizations enable scaling to much larger networks than before. We also present a simple parallelization strategy for distributed subgraph counting on smaller networks. The new additions let us use subgraph counts as graph signatures for a large network collection, and we analyze this collection using various subgraph count-based graph analytics.

关键词： Fascia Approximation methods Dynamic programming Heuristic algorithms Peer-to-peer computing Color image color analysis

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Post processing for dense stereo matching by iterative local plane fitting

Post processing for dense stereo matching by iterative local...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Hongbo Lu Haibo Meng Kun Du Yuan Sun Yuanchao Xu Zhimin Zhang University of Chinese Academy of Sciences Beijing China ISKL Computer Architecture ICT CAS Beijing China Engineering Research Center of WCD NJUPT Nanjing China

Disparity refinement is an essential step of local stereo matching methods to produce fine dense disparity maps. The inherent defect of local stereo methods results in erroneous disparity in occluded areas. In this paper, we present a novel post processing method which can effectively improve the accuracy of dense disparity maps by rectifying disparity errors iteratively. Invalid disparities are first detected by left-right consistency check and color-disparity consistency check. For each invalid pixel, supports from valid pixels in the neighborhood are collected to determine the plane parameters of the local window. An iterative strategy is adopted to gradually propagate disparity information from valid pixels to invalid areas. We apply the proposed method to disparity maps produced by two recent stereo matching methods, and compare the refining results with other post processing methods. Experimental results show the effectiveness of our method in improving dense disparity maps.

关键词： Venus image color analysis Stereo vision Error analysis Fitting Reliability Proposals

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