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共 46 条记录，以下是21-30 订阅

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Automatic Detection and Classification of Tuberculosis Bacilli from Camera-enabled Smartphone Microscopic images 4

Automatic Detection and Classification of Tuberculosis Bacil...

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4th IEEE international conference on parallel, distributed and Grid Computing (IEEE PDGC)

作者： Shah, Mi Mishra, S. Sarkar, Malay Sudarshan, S. K. Jaypee Univ Informat Technol Dept Biotechnol & Bioinformat Solon 173215 Himachal Prades India Indira Gandhi Med Coll Shimla 171001 Himachal Prades India

ISBN: (纸本)9781509036691

Sputum smear conventional microscopy (CM) is used as primary bacteriological test for detection of TB. this technique is the most preferred technique in low and middle income countries due to its availability as well as accessibility. Manual screening of bacilli using CM is time consuming and labor intensive. As a result, the sensitivity of TB detection is compromised leading to misdiagnosis 33-50% of active cases. Automated methods can increase the sensitivity and specificity of TB detection. Currently, the remote areas of TB-endemic developing countries have easy accessibility to portable and camera-enabled Smartphone microscope for capturing images from ZN-stained smear slide. In this paper, the performance of watershed segmentation method for detection and classification of bacilli from camera-enable Smartphone microscopic images is presented. Several preprocessing techniques have been implemented prior to watershed segmentation. Current method has achieved the sensitivity and specificity of 93.3% and 87% respectively for classifying an image as TB positive or negative.

关键词： TB diagnosis Bacilli detection Watershed segmentation ZN-stainin Mobile Microscopy image processing

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image Steganography Using Enhanced LSB Substitution Technique 4

Image Steganography Using Enhanced LSB Substitution Techniqu...

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4th IEEE international conference on parallel, distributed and Grid Computing (IEEE PDGC)

作者： Arora, Arran Singh, Manish Pratap thakral, Prateek Jarwal, Naveen Natl Inst Technol Dept Comp Applicat Kurukshetra Haryana India

ISBN: (纸本)9781509036691

Advancement of technology and rapid Internet made information to travel over the world in an easy and economical way. this has made people to anguish about their privacy. Steganography is a technique that thwarts unauthorized users to have access to the crucial data. there are various steganographic methods that users can use to hide and mix information within other information that make it arduous to recognize by unauthorised users. this paper gives an overview of LSB technique of steganography and further we proposed and implemented a unique algorithm to base steganography which is an enhanced and improved technique better in all aspects. the paper further compares our proposed enhanced technique with the existing LSB technique on various parameters to show effective and satisfactory results.

关键词： image Steganography PSNR Ratio NNE LSB

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MRI Denoising Using Non-Local PCA with DWT 4

MRI Denoising Using Non-Local PCA with DWT

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4th IEEE international conference on parallel, distributed and Grid Computing (IEEE PDGC)

作者： Kaur, Sumeet Kaur, Samandeep Yadavindra Coll Engn Comp Engn Sect Talwandi Sabo Punjab India

ISBN: (纸本)9781509036691

Removing noise from original image is fundamental issue of image denoising. there are number of existing image denoising methods. Each method follows its own unique approach and each method has its own merits and limitations. In this paper, denoising of MR images (Magnetic Resonance Imaging) problem is solved by using a combined approach of non local Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT). Non local principal component analysis follows a patch based approach to remove the noise then discrete wavelet transform is applied to further improve. denoised image to get more denoised MR image. the results reveal that the proposed algorithm provides better peak signal to noise ratio, structural similarity index and some other parameters along with more effectively denoising the MR images that also preserve the details of original image better. the results are calculated in terms of peak signal to noise ratio (PSNR), structural similarity index (SSIM), image enhancement factor (IEF), correlation coefficient (CC), root mean square error (RMSE) and mean square error (MSE).

关键词： Magnetic Resonance Imaging(MRI) Non local Principal Component Analysis (PCA) Discrete wavelet transform (DWT) Peak signal to noise ratio (PSNR) Structural similarity index (SSIM) image enhancement factor (IEF) Correlation coefficient (CC) Root mean square error (RMSE) mean square error (MSE)

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Heterogeneous parallel Implementation of Single image Super Resolution using Transformed Self-Exemplars On Multicore & TitanX GPU 4

Heterogeneous Parallel Implementation of Single Image Super ...

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4th IEEE international conference on parallel, distributed and Grid Computing (IEEE PDGC)

作者： Tanay, K. Chaitanya Pavan Kartheek, P. D. Baruah, P. K. Khanna, Srikanth Chandrasekaran, V. Sri Sathya Sai Inst Higher Learning Prasanthi Nil Anantapur 515134 Andhra Pradesh India

ISBN: (纸本)9781509036691

Super-resolution (SR) can he defined as a method of reconstructing high resolution(HR) image by increasing spatial resolution of one or more low resolution(LR) image counterparts. SR is widely applied in areas like satellite imaging, drones, surveillance and medical imaging etc. SR techniques can be broadly classified as external database driven or internal database driven approaches. the first approach is time consuming during training phase, in learning LR-HR patch relationship but computes fast during testing phase. the second approach directly constructs the super resolved image from existing LR image without the need of any training procedures but found to be computationally intensive during test time. this paper focuses on reducing the computation time of transformed self exemplar based internal database driven technique [1] that uses 3D scene geometry and internal image characteristics for super resolution by exploiting its highly parallelizable nature. On parallelizing the original algorithm we achieved a speedup of 6 on multi-core, upto 10 on GPU, around 14 on hybrid platform of multi-core and GPU. Using our hybrid implementation we can achieve 32x super resolution factor. We compare our results with SRCNN[2] (Super Resolution Convolution Neural Network) an external database SR technique which has a very good performance among the current start-of-the-art SR methods.

关键词： Super Resolution LR HR self exemplar 3D scene geometry GPU Multicore SRCNN

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Enabling Factor Analysis on thousand-Subject Neuroimaging Datasets 4

Enabling Factor Analysis on Thousand-Subject Neuroimaging Da...

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4th IEEE international conference on Big Data (Big Data)

作者： Anderson, Michael J. Capota, Mihai Turek, Javier S. Zhu, Xia Willke, theodore L. Wang, Yida Chen, Po-Hsuan Manning, Jeremy R. Ramadge, Peter J. Norman, Kenneth A. Intel Corp Parallel Comp Lab Hillsboro OR 97124 USA Princeton Univ Princeton NJ 08544 USA Dartmouth Coll Hanover NH 03755 USA

ISBN: (纸本)9781467390057

the scale of functional magnetic resonance image data is rapidly increasing as large multi-subject datasets are becoming widely available and high-resolution scanners are adopted. the inherent low-dimensionality of the information in this data has led neuroscientists to consider factor analysis methods to extract and analyze the underlying brain activity. In this work, we consider two recent multi-subject factor analysis methods: the Shared Response Model and the Hierarchical Topographic Factor Analysis. We perform analytical, algorithmic, and code optimization to enable multi-node parallel implementations to scale. Single-node improvements result in 99x and 2062x speedups on the two methods, and enables the processing of larger datasets. Our distributed implementations show strong scaling of 3.3x and 5.5x respectively with 20 nodes on real datasets. We demonstrate weak scaling on a synthetic dataset with 1024 subjects, equivalent in size to the biggest fMRI dataset collected until now, on up to 1024 nodes and 32,768 cores.

关键词： functional Magnetic Resonance Imaging Multi-subject Analysis Scaling Factor Analysis

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A Review on parallel Medical image processing on GPU 4

A Review on Parallel Medical Image Processing on GPU

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4th international conference on Software Engineering and Computer Systems (ICSECS)

作者： Khor, Hui Liang Liew, Siau-Chuin Zain, Jasni Mohd. Univ Malaysia Pahang Fac Comp Syst & Software Engn Lebuhraya Tun Razak Kuantan 26300 Pahang Darul Ma Malaysia

ISBN: (纸本)9781467367226

An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing. Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. this review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. the review concludes that most medical image processing methods may benefit from GPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.

关键词： parallel computing Medical image processing GPU multicores

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A review on parallel medical image processing on GPU

A review on parallel medical image processing on GPU

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international conference on Software Engineering and Computer Systems (ICSECS)

作者： Hui Liang Khor Siau-Chuin Liew Jasni Mohd Zain Faculty of Computer Systems and Software Engineering University Malaysia Pahang Lebuhraya Tun Razak Malaysia

关键词： Graphics processing units Instruction sets Synchronization Biomedical imaging parallel processing Algorithm design and analysis Biomedical image processing

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Model-based estimation of microscopic anisotropy in macroscopically isotropic substrates using diffusion MRI 24th

Model-based estimation of microscopic anisotropy in macrosco...

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24th international conference on Information processing in Medical Imaging, IPMI 2015

作者： Ianuş, Andrada Drobnjak, ivana Alexander, Daniel C. Centre for Medical Image Computing University College London London United Kingdom

Non-invasive estimation of cell size and shape is a key challenge in diffusion MRI. Changes in cell size and shape discriminate functional areas in the brain and can highlight different degrees of malignancy in cancer tumours. Consequently various methods have emerged recently that aim to measure the microscopic anisotropy of porous media such as biological tissue and aim to reflect pore eccentricity, the simplest shape feature. However, current methods assume a substrate of identical pores, and are strongly influenced by non-trivial size distribution. this paper presents a model-based approach that provides estimates of pore size and shape from diffusion MRI data. the technique uses a geometric model of randomly oriented finite cylinders with gamma distributed radii. We use Monte Carlo simulation to generate synthetic data in substrates consisting of randomly oriented cuboids with various size distributions and eccentricities. We compare the sensitivity of single and double pulsed field gradient (sPFG and dPFG) sequences to the size distribution and eccentricity and further compare different protocols of dPFG sequences with parallel and/or perpendicular pairs of gradients. the key result demonstrates that this model-based approach can provide features of pore shape (specifically eccentricity) that are independent of the size distribution unlike previous attempts to characterise microscopic anisotropy. We show further that explicitly accounting for size distribution is necessary for accurate estimates of average size and eccentricity, and a model that assumes a single size fails to recover the ground truth values. We find the most accurate parameter estimates for dPFG sequences with mixed parallel and perpendicular gradients, nevertheless all other sequences, including sPFG, show sensitivity as well. © Springer international Publishing Switzerland 2015.

关键词： Magnetic resonance imaging

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An Improved Dynamic Trust Model for distributed System 4

An Improved Dynamic Trust Model for Distributed System

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4th international conference on Automation, Communication, Architectonics and Materials (ACAM)

作者： Ye Chongyang Zhuang Yi Nanjing Univ Aeronaut & Astronaut Nanjing Jiangsu Peoples R China

ISBN: (纸本)9783038352891

the parallel, sharing and high speed distributed system has become the mainstream of current system architecture, the characteristics of uncentralized management makes more and more people take flexible operations. However, as the nodes in the system are not bound by a central server and resource sharing is a node's voluntary behavior, the traditional centralized mechanism is not suitable for large-scale distributed system. Aiming at this problem, this paper proposes an improved dynamic trust model for distributed system (IDTrust) to quantify and evaluate the credible degree between nodes. the analysis and simulation results show that the effectiveness of contain malicious nodes and the security aspects of IDTrust are superior to those of current typical methods.

关键词： large-scale distributed system dynamic trust model credible

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Storm System Database: A Big Data Approach to Moving Object Databases

Storm System Database: A Big Data Approach to Moving Object ...

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4th international conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Olsen, Brian McKenney, Mark So Illinois Univ Dept Comp Sci Edwardsville IL 62026 USA

ISBN: (纸本)9780769550121

Rainfall data is often collected by measuring the amount of precipitation collected in a physical container at a site. Such methods provide precise data for those sites, but are limited in granularity to the number and placement of collection devices. We use radar images of storm systems that are publicly available and provide rainfall estimates for large regions of the globe, but at the cost of loss of precision. We present a moving object database called Storm DB that stores decibel measurements of rain clouds as moving regions, ie., we store a single rain cloud as a region that changes shape and position over time. Storm DB is a prototype system that answers rain amount queries over a user defined time duration for any point in the continental United States. In other words, a user can ask the database for the amount of rainfall that fell at any point in the US over a specified time window. Although this single query seems straightforward, it is complicated due to the expected size of the dataset: storm clouds are numerous, radar images are available in high resolution, and our system will collect data over a large timeframe;thus, we expect the number and size of moving regions representing storm clouds to be large. To implement our proposed query, we bring together the following concepts: (i) image processing to retrieve storm clouds from radar images, (ii) interpolation mechanisms to construct moving regions with infinite temporal resolution from region snapshots, (iii) transformations to compute exact point in moving polygon queries using 2-dimensional rather than 3-dimensional algorithms, (iv) GPU algorithms for massively parallel computation of the duration that a point lies inside a moving polygon, and (v) map/reduce algorithms to provide scalability. the resulting prototype lays the groundwork for building big data solutions for moving object databases.

关键词： graphics processing units image processing query processing radar imaging visual databases

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