LoG#

class zrad.filtering.spatial.LoG(padding_type, sigma_mm, cutoff, dimensionality)[source]#

Laplacian-of-Gaussian filter for blob and edge enhancement.

The image is Gaussian-smoothed at a physical scale and then transformed with the Laplacian operator. This highlights intensity transitions and blob-like structures at the configured scale.

Parameters:

  • padding_type ({"constant", "nearest", "wrap", "reflect"}) – Boundary handling mode used during convolution.

  • sigma_mm (float) – Gaussian standard deviation in millimetres.

  • cutoff (float) – Kernel truncation radius in standard deviations.

  • dimensionality ({"2D", "3D"}) – Apply the filter slice-wise in 2D or volumetrically in 3D.

Methods

apply(image)

Apply the filter to an image or set RoiData.filtered_image.

get_params()

Return filter parameters mapped to their configured values.
LoG.apply(image)#

Apply the filter to an image or set RoiData.filtered_image.

Parameters:

image (Image or RoiData) – Input image to filter. If RoiData is supplied, filtering is applied to image.image and the result is stored as filtered_image in the returned ROI data. Existing intensity, texture, and IVH prepared fields are cleared.

Returns:

filtered – Filtered image, or ROI data with filtered_image updated.

Return type:

Image or RoiData

LoG.get_params()#

Return filter parameters mapped to their configured values.

Returns:

params – Constructor parameters stored by the filter instance.

Return type:

dict