12910
Eirik Myklebost
Finite-Difference Time-Domain (FDTD) is a popular technique for modeling computational electrodynamics, and is used within many research areas, such as the development of antennas, ultrasound imaging, and seismic wave propagation. Simulating large domains can however be very compute and memory demanding, which has motivated the use of cluster computing, and lately also the use of […]
View View   Download Download (PDF)   
Andrew A. Haigh, Eric C. McCreath
The realistic simulation of ultrasound wave propagation is computationally intensive. The large size of the grid and low degree of reuse of data means that it places a great demand on memory bandwidth. Graphics Processing Units (GPUs) have attracted attention for performing scientific calculations due to their potential for efficiently performing large numbers of floating […]
View View   Download Download (PDF)   
Tord Oygard
Ultrasound is a flexible medical imaging modality with many uses, one of them being intra-operative imaging for use in navigation. In order to obtain the highest possible spatial resolution and avoiding big, clunky 3D ultra-sound probes, reconstruction of many 2D ultrasound images obtained by a conventional 2D ultrasound probe with a tracking system attached has […]
View View   Download Download (PDF)   
J.-B. Keck, M. Chabanas
A miniature 3D tracked ultrasonic probe has been developed to acquire intra-articular cartilage images under arthroscopic surgical conditions. The aim is to detect cartilaginous lesions (arthritis) and quantify their precise sizes and locations to help the clinician in his diagnostic and his therapeutic decision making. The ultrasonic transducer is tracked by an optical sensor, which […]
View View   Download Download (PDF)   
S. Kostopoulos, K. Sidiropoulos, D. Glotsos, N. Dimitropoulos, I. Kalatzis, P. Asvestas and D. Cavouras
The aim of this study was to design a pattern recognition system for assisting the diagnosis of breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology was employed based on commercial Graphics Processing Unit (GPU) cards and parallel programming. An experienced radiologist outlined breast lesions on both […]
View View   Download Download (PDF)   
B. Dolwithayakul, C. Chantrapornchai, N. Chumchob
The ultrasound videos are mainly contaminated by multiplicative noises but also contaminated with additive noises. As the past few decades, there are some studies to remove the noises from ultrasound images as in the JY model [1] and the variational model which removes both types of noises. However, denoising these noises from the ultrasound video […]
View View   Download Download (PDF)   
David Pierson Bradway, Michael Johannes Pihl, Andreas Krebs, Borislav Gueorguiev Tomov, Carsten Straso Kjaer, Svetoslav Ivanov Nikolov, Jorgen Arendt Jensen
Rapid estimation of blood velocity and visualization of complex flow patterns are important for clinical use of diagnostic ultrasound. This paper presents real-time processing for two-dimensional (2-D) vector flow imaging which utilizes an off-the-shelf graphics processing unit (GPU). In this work, Open Computing Language (OpenCL) is used to estimate 2-D vector velocity flow in vivo […]
View View   Download Download (PDF)   
Tim Idzenga, Evghenii Gaburov, Willem Vermin, Jan Menssen, Chris L. de Korte
Deformation of tissue can be accurately estimated from radio-frequency ultrasound data using a 2-dimensional normalized cross correlation (NCC)-based algorithm. This procedure, however, is very computationally time-consuming. A major time reduction can be achieved by parallelizing the numerous computations of NCC. In this paper, two approaches for parallelization have been investigated: the OpenMP interface on a […]
Banpot Dolwithayakul, Chantana Chantrapornchai, Noppadol Chumchob
The ultrasound image sequences are not only majorly contaminated by multiplicative noises but they are also usually contaminated with additive noises. As in the past few decades, there were some works, which had focused on removing the noises from ultrasound images, such as in the JY model [1] and in the variational model, which were […]
View View   Download Download (PDF)   
Yannick van Bavel
Ultrasound scanners are often used in medical diagnostics for visualising body parts without entering the body. An image is created by visualising reflections from an ultrasound pulse, transmitted into the body. Current scanners use a scanning which creates an image line by line, using focused pulses on each line separately. This method results in high […]
View View   Download Download (PDF)   
M. Walczak, M. Lewandowski, N. Zolek
Our goal is to develop a complete ultrasound platform based on real-time SAFT (Synthetic Aperture Focusing Technique) GPU processing. We are planning to integrate all the ultrasound modules and processing resources (GPU) in a single rack enclosure with the PCIe switch fabric backplane. The first developed module (RX64) provides acquisition and streaming of 64 ultrasound […]
View View   Download Download (PDF)   
Mattias Machwirth
The project evaluates how well a haptic device can be used to interact with a visualization of volumetric data. Since the interface to the haptic device require explicit surface descriptions, triangles had to be constructed from the volumetric data. The algorithm used to extract these triangles is marching cubes. The triangles produced by marching cubes […]
View View   Download Download (PDF)   
Page 1 of 612345...Last »

* * *

* * *

Like us on Facebook

HGPU group

166 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1272 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: