GPUCorrel: A GPU accelerated Digital Image Correlation software written in Python

GPU Accelerated Medical Image Registration Techniques

Graphics processing unit (GPUs) are used in wide range of application now a days particularly Medical image processing in GPU becomes popular recently. Medical imaging procedures are often computationally demanding due to three dimensional data sets. With enhancing performances of graphic processors, improved programming support, GPU has emerged as a competitive parallel computing platform for ...

Ncorr: Open-Source 2D Digital Image Correlation Matlab Software

Digital Image Correlation (DIC) is an important and widely used non-contact technique for measuring material deformation. Considerable progress has been made in recent decades in both developing new experimental DIC techniques and in enhancing the performance of the relevant computational algorithms. Despite this progress, there is a distinct lack of a freely available, high-quality, flexible D...

A GPU- Accelerated Framework for Image Processing and Computer Vision

This paper presents and briefly describes the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multiplatform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU technologies. GpuCV is des...

GPU Accelerated Image Registration in Two and Three Dimensions

Medical image registration tasks of large volume datasets, especially in the non-rigid case, often put a heavy burden on computing resources. GPUs are a promising new approach to address computational intensive image processing tasks. We investigate recently introduced GPU hardware features that accelerate 2D and 3D rigid and nonrigid registration tasks. Our implementation is entirely GPU based.

Digital Image Correlation