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Creating Mask ROIs

Mask ROIs can be used in a number of different contexts — such as for training Deep Learning models, computing Watersheds, and generating vector fields for an in-depth analysis. When applied, masks limit computations to a subset of the original data, which can help reduce processing times and increase accuracy.

You can create a mask ROI one of two ways. You can remove all labeled voxels from a selected region of interest that are outside of a shape (see Creating Mask ROIs by Removing Labeled Voxels from an ROI), or you can add labeled voxels to a selected ROI that are inside a shape (see Creating Mask ROIs by Adding Labeled Voxels to an ROI).

 

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