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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)



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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