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International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)

作者： Ramandeep Singh Dehal Chirag Munjal Arquish Ali Ansari Anup Singh Kushwaha MRU Faridabad

ISBN: (纸本)9781538641200

In this research paper, we have studied Compute Unified Device Architecture which was developed by NVIDIA for its GPUs. It is a graphic library that provides a set of APIs' which lets us take advantage of the GPU to render graphics on the computer screen. We have listed the advantages of CUDA over OpenGL & discussed the CUDA process flow & model overview leading to the reviews on its applications i.e. MRI, Ultrasound, Tomography, x-Rays, CT Scan, DWT-PCA Based image Fusion, Morphological image processing, parallelizing Multi-Sensor, Pyramidal image blending, parallel wavelet algorithm on GPU using CUDA.

关键词： Graphics processing units Instruction sets Kernel Computed tomography Message systems Ultrasonic imaging

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A Novel Highly parallel Algorithm For The Detection And Tracking Of Chemical Gas Plumes Using Hyperspectral Video Sequences

A Novel Highly Parallel Algorithm For The Detection And Trac...

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Workshop on Hyperspectral image and Signal processing: Evolution in Remote Sensing, WHISPERS

作者： MarÍa DÍaz Jocelyn Chanussot Raúl Guerra Sebastián López Roberto Sarmiento Andrea L. Bertozzi IUMA University Institute of Applied Microelectronic Univ. Las Palmas de Gran Canaria Spain Grenoble INP GIPSA-lab Univ. Grenoble Alpes CNRS Grenoble France Department of Mathematics University of California Los Angeles Los Angeles USA

ISBN: (纸本)9781728115825

Multitemporal hyperspectral images provide detailed spectral information that makes them particularly suitable for the detection and tracking of chemical gas plumes. However, due to the high dimensionality of the data to process, classical video processing techniques do not ensure a real-time performance, which makes imperative the development of new advanced and computationally efficient algorithms. In this paper, we propose a novel method for the detection and tracking of chemical gas plumes, recorded in hyperspectral video sequences, which has been specially designed for being easily parallelizable in hardware devices for applications under realtime constraints. The identification of the gas plume presence has been tackled as a spectral change detection problem using the temporal redundancy of two consecutive frames. To maximize spectral differences, the first derivative of each frame pixel is computed and compared with its homologous pixel in the next frame measuring the spectral angle between them. We have applied the proposed methodology to two real video sequences. The results obtained support the benefits of our proposal.

关键词： Hyperspectral imaging Video sequences Chemicals Proposals Real-time systems Redundancy

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parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL 7

Parallel exploitation of a spatial-spectral classification a...

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Conference on High-Performance Computing in Geoscience and Remote Sensing Vii

作者： Lazcano, R. Madronal, D. Fabelo, H. Ortega, S. Salvador, R. Callico, G. M. Juarez, E. Sanz, C. Univ Politecn Madrid Ctr Software Technol & Multimedia Syst CITSEM Madrid Spain ULPGC Res Inst Appl Microelect IUMA Las Palmas Gran Canaria Spain

ISBN: (纸本)9781510613256;9781510613249

Hyperspectral imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVC-CAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

关键词： Hyperspectral imaging Spatial-spectral classification RVC-CAL Real-time processing parallelism exploitation

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Development and future trends in the application of visualization toolkit (VTK): The case for medical image 3D reconstruction

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AIP Conference Proceedings 2019年第1期2092卷

作者： Welsey Daniel C. Advincula Jose Antonio G. Choco Kryzz Amiel G. Magpantay Leonard Angelo N. Sabellina, iiI Jolo Gerard Miel F. Tolentino Renann G. Baldovino Nilo T. Bugtai Aaron Raymond See Yi-Chun Du 1Manufacturing Engineering and Management (MEM) Department De La Salle University 2401 Taft Avenue 0922 Manila Philippines 2Department of Electrical Engineering Southern Taiwan University of Science and Technology No. 1 Nantai Street Yongkang District Tainan City Taiwan 710

Three-dimensional reconstruction of medical images plays a vital role in clinical medicine and medical research. It serves as a powerful tool to help doctors analyze multiple 2D medical images in a 3D perspective. The developed 3D model offers a faster and accurate approach in clinical diagnosis and therapy. Before, the development of 3D reconstruction programs it has always been a challenge to visualize in a 3D perspective but with the advent of powerful computing and graphics processing, medical imaging equipment development is on the rise. The advancement of 3D image reconstruction is not only due to the innovative hardware, but also because of the increase in open-source platforms or libraries, such as visualization toolkit (VTK), that assist on its development to provide an information visualization framework and advanced 3D modeling techniques. VTK is an object-oriented 3D graphics software program that is free to obtain and used both for open- and closed-source applications such as 3D computer graphics, image processing, and visualization. In medical imaging, data from ultrasound systems, magnetic resonance imaging (MRI), and computed tomography (CT) scans can be managed in VTK. Different algorithms of image processing such as color mapping, image re-slicing or resampling, iso-contouring, thresholding, and other algorithms can be utilized to make volume images from the data. Subsequently, data presentation is simplified with the data reconstruction through the use of supplemental software for analysis. VTK library contains a large number of filters, which are multi-threaded to facilitate parallel processing and interpretation. In this paper, recent technologies on the application of VTK for 3D reconstruction of biomedical images will be presented. Moreover, current methodologies will be discussed to clearly understand the different integral steps needed in image data conversion.

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Optimal control design of turbo spin-echo sequences with applications to parallel-transmit systems

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MAGNETIC RESONANCE IN MEDICINE 2017年第1期77卷 361-373页

作者： Sbrizzi, Alessandro Hoogduin, Hans Hajnal, Joseph V. van den Berg, Cornelis A. T. Luijten, Peter R. Malik, Shaihan J. Univ Med Ctr Utrecht Imaging Div Utrecht Netherlands Kings Coll London Dept Biomed Engn Div Imaging Sci London England

PurposeThe design of turbo spin-echo sequences is modeled as a dynamic optimization problem which includes the case of inhomogeneous transmit radiofrequency fields. This problem is efficiently solved by optimal control techniques making it possible to design patient-specific sequences online. Theory and MethodsThe extended phase graph formalism is employed to model the signal evolution. The design problem is cast as an optimal control problem and an efficient numerical procedure for its solution is given. The numerical and experimental tests address standard multiecho sequences and pTx configurations. ResultsStandard, analytically derived flip angle trains are recovered by the numerical optimal control approach. New sequences are designed where constraints on radiofrequency total and peak power are included. In the case of parallel transmit application, the method is able to calculate the optimal echo train for two-dimensional and three-dimensional turbo spin echo sequences in the order of 10 s with a single central processing unit (CPU) implementation. The image contrast is maintained through the whole field of view despite inhomogeneities of the radiofrequency fields. ConclusionThe optimal control design sheds new light on the sequence design process and makes it possible to design sequences in an online, patient-specific fashion. Magn Reson Med 77:361-373, 2017. (c) 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine

关键词： optimal control extended phase graph parallel transmit radiofrequency direct signal control fast spin-echo turbo spin-echo

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Camera Orientation Estimation Using Motion Based Vanishing Point Detection for Automatic Driving Assistance System

Camera Orientation Estimation Using Motion Based Vanishing P...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Jo, Youngran Jang, Jinbeum Paik, Joonki Chung Ang Univ Grad Sch Adv Imaging Sci Multimedia & Film Image Proc & Intelligent Syst Lab Seoul South Korea

ISBN: (纸本)9781538630259

This paper presents a camera orientation estimation method based on 3-line RANSAC using motion vector in a driving straight ahead vehicle. The proposed method consists of three steps: i) motion vector and z-axis vanishing point estimation using feature extraction and matching, ii) line detection and classification using 3-line RANSAC algorithm, and iii) camera orientation estimation with vanishing points using classified lines. The experimental result shows proposed method effectively estimate camera orientation parameter. Therefore, the proposed method can be applied in vehicle systems for automatic driving assistance system.

关键词： Cameras Estimation Calibration Classification algorithms parallel processing Computer vision Real-time systems

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Towards autonomous photonic reservoir computer based on frequency parallelism of neurons 2

Towards autonomous photonic reservoir computer based on freq...

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Conference on Real-time Measurements, Rogue Phenomena, and Single-Shot applications ii

作者： Akrout, Akram Antonik, Piotr Haelterman, Marc Massar, Serge Univ Libre Bruxelles Lab Informat Quant 50 Ave FD RooseveltCP 224 B-1050 Brussels Belgium Univ Libre Bruxelles Serv OPERA Photon 50 Ave FD RooseveltCP 194-5 B-1050 Brussels Belgium

ISBN: (纸本)9781510606197;9781510606203

Reservoir Computing is a bio-inspired computational paradigm particularly well adapted to time-dependent signal processing. The past years have seen the realisation of photonic reservoir computers with performance comparable to digital algorithms. Most of these works are based on delay dynamical systems in which the photonic neurons are treated sequentially. We have recently realised an experimental system based on the concept of frequency multiplexing, in which the neurons are materialised as the amplitude of light at different frequencies. In this system the neurons are processed in parallel, making it in principle much faster than the sequential systems. In most of the works up to now the output of the reservoir is implemented using slow digital offline post-processing. This is also the case of our recent experiment on frequency parallelism. Here we demonstrate, using numerical simulations, the possibility of an analogue electronic readout layer for this system. Our simulations take into account all the experimental limitations of the setup, e.g. sampling rates, device bandwidths, resolutions, and noise. The results obtained are comparable to those produced with the same architecture and a digital output layer. The proposed setup is thus an important step towards analog, low footprint, all-optical information processing. Moreover parallel processing will be necessary for high bandwidth applications.

关键词： Reservoir computing frequency multiplexing parallel system analogue readout numerical simulations

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Blind quality assessment of three-dimensional images using joint statistics of binocular rivalry and orientation-tuned responses

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JOURNAL OF ELECTRONIC imaging 2018年第4期27卷 043016-043016页

作者： Ma, Jian An, Ping Shen, Liquan Li, Kai Shanghai Maritime Univ Inst Logist Sci & Engn Shanghai Peoples R China Shanghai Univ Shanghai Inst Adv Commun & Data Sci Sch Commun & Informat Engn Shanghai Shanghai Peoples R China Minist Educ Key Lab Adv Displays & Syst Applicat Shanghai Peoples R China

Perceptual quality assessment of a three-dimensional (3-D) image is one of the most important tasks in various applications such as 3-D image coding, processing, enhancement, and monitoring system. But objective quality assessment of 3-D images is still a challenging task. Especially, blind quality assessment of 3-D images encounters an arduous challenge due to lack of prior information about the original images. To solve this problem, we propose a blind 3-D images' quality evaluator by simulating binocular rivalry and orientation responses of the human visual system. As a main technical contribution of this research, both the low- and high-level binocular rivalry responses (BRR), as well as binocular orientation-tuned (BOT) responses, are considered for blind quality assessment of 3-D images. Specifically, the self-similarity of the BRR and BOT responses is extracted from the distorted 3-D images, which will change in the presence of distortions. Subsequently, all quality-aware features are mapped to subjective quality scores of the distorted 3-D images via using support vector regression. The performance of our algorithm is evaluated over two popular LIVE 3-D phase I and phase ii databases and shown to be competitive with the state-of-the-art algorithms. (C) 2018 SPIE and IS&T

关键词： three-dimensional image blind image quality assessment binocular rivalry binocular orientation tuned support vector regression

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Open-source software platform for medical image segmentation applications 13

Open-source software platform for medical image segmentation...

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13th International Conference on Medical Information processing and Analysis

作者： Namias, R. D'Amato, J. P. del Fresno, M. UNR CONICET UAM France CIFASIS Rosario Santa Fe Argentina Univ Nacl Ctr Inst PLADEMA Tandil Argentina Consejo Nacl Invest Cient & Tecn Buenos Aires DF Argentina CIC PBA Buenos Aires DF Argentina

ISBN: (数字)9781510616349

ISBN: (纸本)9781510616349

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We include the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

关键词： Medical imaging Analysis Multiple Segmentation Framework parallel Segmentation

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FPGA acceleration of Hyperspectral image processing for High-Speed Detection applications 50

FPGA acceleration of Hyperspectral Image Processing for High...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Vellas, Simon Lentaris, George Maragos, Konstantinos Soudris, Dimitrios Kandylakis, Zacharias Karantzalos, Konstantinos Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece Natl Tech Univ Athens Sch Rural & Surveying Engn Athens Greece

ISBN: (纸本)9781467368537

Recent advances in photonics and imaging technology allow the development of cutting-edge, lightweight hyperspectral sensors, both push-broom/line-scanning and snapshot/frame. At the same time, emerging applications in robotics, food inspection, medicine and earth observation are posing critical challenges on real-time processing and computational efficiency, both in terms of accuracy and power consumption. In this direction, in the current paper, we accelerate hyperspectral processing kernels by utilizing FPGAs, i.e., Zynq-7000 SoC, to perform similarity-based matching of spectral signatures. We propose a custom HW architecture based on multi-level parallelization, modularity, and parametric VHDL coding, which allows for in-depth design space exploration and trade-off analysis. Depending on configuration, our implementation processes 22-107 Megapixels per second providing an acceleration of 40-355x vs Intel-i3 CPU and 360-104x vs the embedded ARM Cortex A9, whereas the overall detection quality ranges from 56% to 97% when evaluated with multiple objects and images of 285 spectral channels.

关键词： Field programmable gate arrays Measurement Hyperspectral imaging parallel processing Acceleration Kernel

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