Brief description
Building on the previous exercise, learners now estimate the size of objects in the example image (e.g. width of nuclei).
- Present learners with a specific Z slice from the image, and ask them to estimate the width of a few nuclei:
- first in pixel units (not sure if it's possible to interactively draw a line on matplotlib images to get a width, so may have to present the images with a a pixel grid overlay so they can manually count)
- second in physical units, using the sizes from
bio-io's .physical_pixel_sizes
- Present learners with e.g. a YZ slice from the image, and ask them to estimate the height of a few nuclei:
- first in pixel units
- second in physical units. Ideally this dataset is anisotropic, with a larger pixel size in Z than X/Y.
Learning objective(s)
Covers the 'Physical units from metadata' objective
This exercise will demonstrate the difference between pixel units + physical units, and show learners how to extract this information with bio-io. If we use an anisotropic image (with a lower resolution in Z), it will also demonstrate that units can vary between different image dimensions + how to select the correct dimensions / units for our measurements.
Volunteer(s)
@K-Meech
Brief description
Building on the previous exercise, learners now estimate the size of objects in the example image (e.g. width of nuclei).
bio-io's.physical_pixel_sizesLearning objective(s)
Covers the 'Physical units from metadata' objective
This exercise will demonstrate the difference between pixel units + physical units, and show learners how to extract this information with
bio-io. If we use an anisotropic image (with a lower resolution in Z), it will also demonstrate that units can vary between different image dimensions + how to select the correct dimensions / units for our measurements.Volunteer(s)
@K-Meech