SimpleITK-based object classifier?

[haesleinhuepf]

To give more options for object classification while maintaining the installability of apoc, it might make sense to setup a second ObjectClassfier, that uses internally the regionprops from SimpleITK.

We could then classify objects accorind to their

• maximum
• mean
• median
• minimum
• sigma
• sum
• variance
• bbox
• centroid_0
• elongation
• feret_diameter
• flatness
• roundness
• equivalent_ellipsoid_diameter_0
• equivalent_ellipsoid_diameter_1
• equivalent_spherical_perimeter
• equivalent_spherical_radius
• number_of_pixels
• number_of_pixels_on_border
• perimeter
• perimeter_on_border
• perimeter_on_border_ratio
• principal_axes0
• principal_axes1
• principal_axes2
• principal_axes3
• principal_moments0
• principal_moments1

We could alternatively build this in optionally in the existing object classifier. The user-interface in napari may need a major redesign for this.

See also: https://github.com/haesleinhuepf/napari-simpleitk-image-processing/blob/main/src/napari_simpleitk_image_processing/_simpleitk_image_processing.py#L789

[haesleinhuepf]

Code for this "plugin" lives in this notebook: https://github.com/haesleinhuepf/BioImageAnalysisNotebooks/blob/main/docs/27_cell_classification/apoc_simpleitk_object_classification.ipynb