2. Spot prediction
This is the step performed before detecting the centers of the spots and the is a semantic segmentation masks of the areas were SpotMAX will later look for spots.
This means that if an area in the image is marked as background in this step, spots will not be searched and detected there.
Segmentation of the spots image is performed in two steps:
2.1. Image pre-processing
SpotMAX provides two filters for image pre-processing of the spots signal: blurring (gaussian filter) and a spot detection filter (i.e., Difference of Gaussians).
The gaussian filter can be applied with a different sigma for each dimension, which is very useful when working with anisotropic 3D z-stack data.
The spot detection filter is a Difference of Gaussians filter whose parameters
are automatically calculated from the expected spot size. See the
description of the parameter Sharpen spots signal prior detection for
more details.
2.2. Semantic segmentation
The pre-processed image is used as input to the segmentation model of your choice. SpotMAX will segment the reference channel by using automatic thresholding, SpotMAX AI models, Spotiflow, or any of the models available on the BioImage.IO Model Zoo.
For more details about the available methods for automatic thresholding see this guide Thresholding (scikit-image).
One crucial aspect of SpotMAX is that you can apply the segmentation model
on each input segmented object (e.g., the single cells, a.k.a. “Local”) or on
all the objects in the image (a.k.a. “Aggregated”). See the parameter
Aggregate cells prior analysis to know how to toggle these two modes.
We recommend testing with both modes, but as a rule of thumb if all the reference channel structures are present in all the cells but you have a large intensity variation between objects then using the “Local” mode could be beneficial.
On the other hand, if some of the objects are completely devoid of any reference channel structure aggregating the objects might be the only option.
Note
If you are working with the S. cerevisiase model organism, most of the
times small buds do not have any structure. However, the “Local” will
still work if you annotate mother-bud relationship using our other software
Cell-ACDC. This is because SpotMAX will consider the mother-object
as a single object while the bud is still attached to the mother (i.e.,
before division is annotated). Make sure that you provide the annotations
to SpotMAX with the parameter Table with lineage info end name.