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Abstract

Most state-of-the-art algorithms for filament detection in 3-D image-stacks rely on computing the Hessian matrix around individual pixels and labeling these pixels according to its eigenvalues. This approach, while very effective for clean data, hi which linear structures are nearly cylindrical, loses its effectiveness in the presence of noisy data and irregular structures.

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