The Blob Finder is a popular segmentation operation that is available in arivis. It is a fairly powerful operation because it is quite robust in dealing with noise and uneven backgrounds without the need for additional image pre-processing. The exact details of how this operation works is covered in the help files which we can access by pressing the F1 key on our keyboard.

The first parameter that needs to be set in any segmentation operation is the channel from which the segmentation extracts objects. Most operation only use one channel for segmentation, but some, including the Machine Learning and Deep Learning segmenters can use multiple channel inputs.

When setting up any segmentation operation, we usually have a couple of parameters to set, and we can use the preview to help us set the correct values.

The exact values we used in this case aren't particularly important, by using the preview we can adjust the parameters until the segmentation seems optimal. If we use this pipeline with multiple images it is of course also important to use the same settings for all our images and therefore to also test on a variety of images.

Every segment operation, whether it creates de novo objects or modifies existing ones, uses tags to help us select the objects in downstream pipeline operations. The default tag is the name of the operation, which is fine as a 1st default value but likely not ideal if our pipeline contains several segmentations or object processing operations of the same type, and it is therefore recommended to change the tag to something more appropriate.

Useful tip with regards to naming: start with names that describe the process then narrow down the naming to specific object types. For example, we might start with a tag "DAPI Seg" and then use the tag "Nucleus" once all false positives have been removed.