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Steerable Features for Statistical 3D Dendrite Detection

Steerable Features for Statistical 3D Dendrite Detection,10.1007/978-3-642-04271-3_76,Germán González,François Aguet,François Fleuret,Michael Unser,Pa

Steerable Features for Statistical 3D Dendrite Detection   (Citations: 3)
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Most state-of-the-art algorithms for lament detection in 3{D image-stacks rely on computing the Hessian matrix around indi- vidual pixels and labeling these pixels according to its eigenvalues. This approach, while very eective for clean data in which linear structures are nearly cylindrical, loses its eectiveness in the presence of noisy data and irregular structures. In this paper, we show that using steerable lters to create rotationally invariant features that include higher-order derivatives and training a classier based on these features lets us handle such irregular structures. This can be done reliably and at acceptable computational cost and yields better results than state-of-the-art methods.
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    • ...Most automated delineation techniques rely on a local tubularity measure that can be postulated ap riori (Frangi et al. 1998; Law and Chung 2008), optimized to find specific patterns (Jacob and Unser 2004; Meijering et al. 2004), or learned (Santamaría-Pang et al. 2007; Gonzalez et al. 2009) from training data...
    • ...More specifically, for each voxel, we form a set of feature vectors each of which is made up of steerable filter responses (Gonzalez et al. 2009) and Hessian eigenvalues at a particular scale and an orientation...

    Engin Türetkenet al. Automated Reconstruction of Dendritic and Axonal Trees by Global Optim...

    • ...An alternative approach is to use a bank of steerable filters designed to enhance different orientations and take the maximum over the range of orientations (Freeman et al. 1991; Gonzalez et al. 2009; Jacob and Unser 2004)...

    Paarth Chothaniet al. Automated Tracing of Neurites from Light Microscopy Stacks of Images

    • ...More specifically, we use 3D-steerable features [12] to assign to image points, and to edges connecting them, probabilities of belonging to the tree...
    • ...This measure can be postulated [10, 16], optimized given a mathematical dendrite model [15, 18], or learned [21, 12] from training data...
    • ...We run the dendrite detector of [12] at different image scales to obtain a dendriteness measure for each voxel...

    Germán Gonzálezet al. Delineating trees in noisy 2D images and 3D image-stacks

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