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JulietteFrancovich
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Aug 8, 2025
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This PR add the PixelMaskCollection class, based on the recently added PixelMask.
The main goal for this class is to be able to apply multiple masks to data, returning a dictionary of individual results. You can also combine the contained masks into a single mask by summing them ("sum") or multiplying them ("product").
Masks in a collection can be labelled or anonymous. Labelled is useful when working with pre-defined masks, e.g., 'ventral' and 'dorsal', while anonymous masks are useful when working with an unpredictable number of masks, e.g., ROI definition based on thresholds resulting in multiple separate areas that can be independently labelled.