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GPU accelerated vessel segmentation using Laplacian eigenmaps

with Lin Cheng, Peter Yoon and Jiajia Zhao

Paper presented at IASTED PDCN (2014)
Poster presented at the GPU Technology Conference (2013)

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Synopsis

Laplacian eigenmap is an image segmentation algorithm that began to gain traction in recent years. It involves a generalized eigenvalue problem which extracts high-level features from local neighborhood information. Unfortunately, it is computationally costly to compute eigenvalues of a large linear systems. We make use of general-purpose GPUs to accelerate the segmentation process.

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