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Rapid rabbit: Highly optimized GPU accelerated cone-beam CT reconstruction

Rapid rabbit: Highly optimized GPU accelerated cone-beam CT ...

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IEEE symposium on Nuclear Science (NSS/MIC)

作者： Eric Papenhausen Klaus Mueller Computer Science Department Stony Brook University Stony Brook NY USA

Graphical processing units (GPUs) have become widely adopted in the medical imaging community. The parallel SIMD nature of GPUs maps perfectly to many reconstruction algorithms. Because of this, it is relatively straightforward to parallelize common reconstruction algorithms (e.g. FDK backprojection). This means that significant performance improvements must come from careful memory optimizations, exploiting ASICs and a few other tricks to boost instruction throughput. We present optimizations that build off of previous work to optimize a GPU accelerated FDK backprojection implementation using the RabbitCT dataset.

关键词： graphics processing units Optimization image reconstruction Kernel Instruction sets Acceleration Reconstruction algorithms

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A View-Dependent Stereoscopic System Using Tiled Projection

A View-Dependent Stereoscopic System Using Tiled Projection

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International symposium on Computational Intelligence and Design, ISCID

作者： Feng Chen Yue Liu School of Optoelectronics Beijing Institute of Technology Beijing China

In this paper, we present a novel system which allows its users to see a stereoscopic virtual object. Unlike most existing stereoscopic systems that display the same imagery when watched from different directions, the user's head is tracked in real-time so that the real-time images can be rendered according to the viewing position, which enables the dynamic images to be displayed on the screen and the users can see different parts of a virtual object when wearing a pair of polarized glasses. This creates a more vivid illusion that a real object is set at the physical scene. The key technologies of the proposed system such as depth-image-based head tracking, geometric calibration and view-dependent real-time stereoscopic image rendering are studied and the experimental results proves the performance of the proposed system.

关键词： Head Stereo image processing Cameras Three-dimensional displays Real-time systems Calibration Rendering (computer graphics)

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An analysis of scalable GPU-based ray-guided volume rendering

An analysis of scalable GPU-based ray-guided volume renderin...

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IEEE symposium on Large Data Analysis and Visualization (LDAV)

作者： Thomas Fogal Alexander Schiewe Jens Krüger HPC Group Duisburg-Essen SCI Intel VCI

ISBN: (纸本)9781479924363

Volume rendering continues to be a critical method for analyzing large-scale scalar fields, in disciplines as diverse as biomedical engineering and computational fluid dynamics. Commodity desktop hardware has struggled to keep pace with data size increases, challenging modern visualization software to deliver responsive interactions for O(N 3 ) algorithms such as volume rendering. We target the data type common in these domains: regularly-structured data. In this work, we demonstrate that the major limitation of most volume rendering approaches is their inability to switch the data sampling rate (and thus data size) quickly. Using a volume renderer inspired by recent work, we demonstrate that the actual amount of visualizable data for a scene is typically bound considerably lower than the memory available on a commodity GPU. Our instrumented renderer is used to investigate design decisions typically swept under the rug in volume rendering literature. The renderer is freely available, with binaries for all major platforms as well as full source code, to encourage reproduction and comparison with future research.

关键词： graphics processing units image resolution Abstracts Hardware Rendering (computer graphics) Benchmark testing

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ASCII Art Generation Using the Local Exhaustive Search on the GPU

ASCII Art Generation Using the Local Exhaustive Search on th...

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International symposium on Computing and Networking (CANDAR)

作者： Yuji Takeuchi Daisuke Takafuji Yasuaki Ito Koji Nakano Department of Information Engineering Hiroshima University Higashi-Hiroshima JAPAN Hiroshima Daigaku Higashihiroshima Hiroshima JP

An ASCII art is a matrix of characters that reproduces an original gray-scale image. It is commonly used to represent pseudo gray-scale images in text based messages. Since automatic generation of high quality ASCII art images is very hard, they are usually produced by hand. The main contribution of this paper is to propose a new technique to generate an ASCII art that reproduces the original tone and the details of an input gray-scale image. Our new technique is inspired by the local exhaustive search to optimize binary images for printing based on the characteristic of the human visual system. Although it can generate high quality ASCII art images, a lot of computing time is necessary for the local exhaustive search. Hence, we have implemented our new technique in a GPU to accelerate the computation. The experimental results shows that the GPU implementation can achieve a speedup factor up to 57.1 over the conventional CPU implementation.

关键词： Art graphics processing units Gray-scale Instruction sets Acceleration computer architecture Visual systems

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Use of SIMD Vector Operations to Accelerate Application Code Performance on Low-Powered ARM and Intel Platforms

Use of SIMD Vector Operations to Accelerate Application Code...

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IEEE International symposium on Parallel and Distributed processing Workshops and Phd Forum (IPDPSW)

作者： Gaurav Mitra Beau Johnston Alistair P. Rendell Eric McCreath Jun Zhou Australian National University Canberra ACT AU Griffith University Nathan QLD AU

ISBN: (纸本)9781479913725

Augmenting a processor with special hardware that is able to apply a Single Instruction to Multiple Data(SIMD) at the same time is a cost effective way of improving processor performance. It also offers a means of improving the ratio of processor performance to power usage due to reduced and more effective data movement and intrinsically lower instruction counts. This paper considers and compares the NEON SIMD instruction set used on the ARM Cortex-A series of RISC processors with the SSE2 SIMD instruction set found on Intel platforms within the context of the Open computer Vision (OpenCV) library. The performance obtained using compiler auto-vectorization is compared with that achieved using hand-tuning across a range of five different benchmarks and ten different hardware platforms. On the ARM platforms the hand-tuned NEON benchmarks were between 1.05× and 13.88× faster than the auto-vectorized code, while for the Intel platforms the hand-tuned SSE benchmarks were between 1.34× and 5.54× faster.

关键词： Registers Vectors Benchmark testing image processing graphics processing units Assembly Educational institutions

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A Novel Method for Illumination Normalization for Performance Improvement of Face Recognition System

A Novel Method for Illumination Normalization for Performanc...

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International symposium on Electronic System Design (ISED)

作者： Neelamma K. Patil S. Vasudha Lokesh R. Boregowda Department of Telecommunication Engineering KLES College of Engineering & Technology Belgaum India Honeywell Technology Solutions Bangalore India

As one of the most successful applications of image analysis, face recognition has received significant attention, especially during past few years. Automatic human face recognition has received substantial attention from researchers in biometrics, pattern recognition and computer vision communities. The machine learning and computer graphics communities are also increasingly involved in face recognition. The localization of human faces in digital images is a fundamental step in the process of face recognition. Although the existing automated machine recognition systems have certain level of maturity, but their accomplishments are limited due to real time challenges. For example, face recognition for the images which are acquired in high contrast with different levels of illumination is a critical problem. It is known that image variation due to lighting changes is larger than that, due to different personal identity, because lighting direction alters the relative gray scale distribution of a face image. In handling these types of practical scenarios, the system must be robust enough to deal with dynamic changes in lighting, hence it is equally important to preprocess the images prior to actual processing and experimentations. This paper proposes a novel method of illumination normalization based on histogram of an image and scaling function. It helps in construction of an optimal global lighting space from these images which improve accuracy of face recognition system. The proposed method helps in recognition of sparsely sampled images with different lighting too. Also, most valuable information of an image, i.e. gray scale value, is not discarded and person's discriminative information in face image is strengthened. Hence recognition can be carried out using preserved illumination invariant features.

关键词： Lighting Face Face recognition Histograms image edge detection Databases

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Ultra Fast TOF 3D Reconstruction Using SIMD and Symmetry Superior to GPU Implementation

Ultra Fast TOF 3D Reconstruction Using SIMD and Symmetry Sup...

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IEEE Nuclear Science symposium

作者： Inki Hong Ziad Burbar Siemens Healthcare Knoxville TN USA

TOF PET 3D reconstruction adds another layer of complexity. Thus it becomes a challenge to find the most efficient method to optimize the reconstruction without compromising image quality. In this study, mCT PET scanner data is used for image reconstruction and comparison. This study shows how an ultrafast forward and back projector pair TOF 3D reconstruction is implemented based on Symmetry SIMD Projector (SSP) algorithm. The Symmetry in the algorithm translates to four symmetric relationships;+90° symmetry of the projection angle, mirror-symmetry on the Radial bin axis, symmetry of the integral direction along LOR, symmetry of the oblique segment angle. The use of SIMD allows the access of four data points by one operand which reduces computation time by a factor of four. Therefore, SSP algorithm can ideally reduce the computation time of forward projection and back projection by a factor of 64. The computer hardware used is off the shelf workstation with Intel Xeon E5540 2×CPU, 12GB, 1×GPU Tesla. The reconstructed image size is 400×400×109 pixels. For the same data set, the SSP algorithm using a CPU based reconstruction was able to achieve twice the timing improvement over the standard GPU counterpart.

关键词： image reconstruction graphics processing units Three-dimensional displays Positron emission tomography High definition video Timing Interpolation

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GPU-based real-time imaging software suite for medical ultrasound

GPU-based real-time imaging software suite for medical ultra...

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IEEE symposium (IUS) Ultrasonics

作者： Jung Woo Choe Amin Nikoozadeh Ömer Oralkan Butrus T. Khuri-Yakub Edward L. Ginzton Laboratory Stanford University Stanford CA Department of Electrical and Computer Engineering North Carolina State University Raleigh NC

We developed a GPU-based real-time imaging software suite for medical ultrasound imaging to provide a fast real-time imaging platform for various probe geometries and imaging schemes. The imaging software receives raw RF data from a data acquisition system, and processes them on GPU to reconstruct real-time images. The most general-purpose imaging program in the suite displays three cross-sectional images for arbitrary probe geometry and various imaging schemes including conventional beamforming, synthetic beamforming, and plane-wave compounding. The other imaging programs in the software suite, derived from the general-purpose imaging program, are optimized for their own purposes, such as displaying a rotating B-mode plane and its maximum intensity projection (MIP), photoacoustic imaging, and real-time volume-rendering. Real-time imaging was successfully demonstrated using each of the imaging programs in the software suite.

关键词： Imaging Real-time systems Probes graphics processing units image reconstruction Ultrasonic imaging

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Segmentation of lung region based on using parallel implementation of joint MGRF: Validation on 3D realistic lung phantoms

Segmentation of lung region based on using parallel implemen...

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IEEE International symposium on Biomedical Imaging

作者： Ahmed Soliman Fahmi Khalifa Amir Alansary Georgy Gimel'farb Ayman El-Baz Bioengineering Department University of Louisville Louisville KY USA Department of Computer Science University of Auckland Auckland New Zealand

ISBN: (纸本)9781467364560

The segmentation of the lung tissues in chest Computed Tomography (CT) images is an important step for developing any computer-Aided Diagnostic (CAD) system for lung cancer and other pulmonary diseases. In this paper, we introduce a new framework to generate 3D realistic synthetic phantoms to validate our developed Joint Markov-Gibbs based lung segmentation approach from CT data. Our framework is based on using a 3D generalized Gauss-Markov Random Field (GGMRF) model of voxel intensities with pairwise interaction to model the 3D appearance of the lung tissues. Then, the appearance of the generated 3D phantoms is simulated based on iterative minimization of an energy function that is based on using the learned 3D-GGMRF image model. These 3D realistic phantoms can be used to evaluate the performance of any lung segmentation approach. In this paper, we used the 3D realistic phantoms to evaluate the performance of our developed lung segmentation approach based on using the Dice Similarity Coefficient (DSC) metric and the Receiver Operating Characteristics (ROC). The DSC demonstrated that our approach achieves a mean DSC value of 0.994 ± 0.0034. Moreover, the ROC analysis for our method showed the best performance (area 0.99), while intensity showed the worst performance (area 0.92).

关键词： Lungs image segmentation Phantoms Computed tomography graphics processing units Solid modeling Joints

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Fluid simulation on surfaces in the GPU

Fluid simulation on surfaces in the GPU

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25th Conference on graphics, Patterns and images, SIBGRAPI 2012

作者： Carvalho, Leonardo Andrade, Maria Velho, Luiz IMPA Rio de Janeiro Brazil UFAL Maceió Brazil

ISBN: (纸本)9780769548296

In this paper we present a method to simulate fluids on smooth surfaces of arbitrary topology using a graphics processing unit (GPU). To do this we use the parametrization of Cat mull-Clark subdivision surfaces and obtain the metric information of the distortion caused by this parametrization, so we can calculate differential operators of functions defined on this surface. Then the Navier-Stokes equations on surfaces are solved in the domain of parametrization of each patch. This process can be done in parallel for each point in the discretization of the surface, so the GPU implementation can heavily increase the velocity of computation. © 2012 IEEE.

关键词： graphics processing unit

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