Cuda K-Nn: application to the segmentation of the retinal vasculature within SD-OCT volumes of mice
University of Iowa
University of Iowa, 2013
@article{deng2013cuda,
title={Cuda K-Nn: application to the segmentation of the retinal vasculature within SD-OCT volumes of mice},
author={Deng, Wenxiang},
year={2013},
publisher={University of Iowa}
}
In this work, a speed comparison between GPU-based CUDA k-NN implementation and the ANN implementation has been tested on three sets of medical imaging data. The results show that with higher dimensional data, CUDA-based k-NN approach could have up to two orders of magnitude of speed up. Otherwise, ANN would be a better implementation to use. Also, based on the work of CUDA k-NN, we present two new approaches to segment vasculature in mouse retina using large set of features. They performs better than directly implementing closest previous OCT-based approach. The method using all layer projections would show overall best result with more visible vessels and higher contrast.
February 16, 2014 by hgpu
Your response
You must be logged in to post a comment.




