skimage2.filters.meijering#
- skimage2.filters.meijering(image, sigmas=range(1, 10, 2), alpha=None, black_ridges=True, mode='reflect', cval=0)[source]#
Filter an image with the Meijering neuriteness filter.
This filter can be used to detect continuous ridges, e.g. neurites, wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects.
Calculates the eigenvalues of the Hessian to compute the similarity of an image region to neurites, according to the method described in [1].
- Parameters:
- image(M, N[, âĶ]) ndarray
Array with input image data.
- sigmasiterable of floats, optional
Sigmas used as scales of filter
- alphafloat, optional
Shaping filter constant, that selects maximally flat elongated features. The default, None, selects the optimal value -1/(ndim+1).
- black_ridgesbool, optional
When True (the default), the filter detects black ridges; when False, it detects white ridges.
- mode{âconstantâ, âreflectâ, âwrapâ, ânearestâ, âmirrorâ}, optional
How to handle values outside the image borders.
- cvalfloat, optional
Used in conjunction with mode âconstantâ, the value outside the image boundaries.
- Returns:
- out(M, N[, âĶ]) ndarray
Filtered image (maximum of pixels across all scales).
References
[1]Meijering, E., Jacob, M., Sarria, J. C., Steiner, P., Hirling, H., Unser, M. (2004). Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytometry Part A, 58(2), 167-176. DOI:10.1002/cyto.a.20022
