DREAM.3D v6 User Manual
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Processing (Cleanup)
Often when performing a serial sectioning experiment (especially in the FIB-SEM), the sample is overscanned resulting in a border of bad data around the sample. This Filter attempts to identify the sample within the overscanned volume. The Filter makes the assumption that there is only one contiguous set of Cells that belong to the sample. The Filter requires that the user has already thresheld the data to determine which Cells are good and which are bad. The algorithm for the identification of the sample is then as follows:
If Fill Holes is set to true:
Note: if there are in fact "holes" in the sample, then this Filter will "close" them (if Fill Holes is set to true) by calling all the Cells "inside" the sample good. If the user wants to reidentify those holes, then reuse the threshold Filter with the criteria of GoodVoxels = 1 and whatever original criteria identified the "holes", as this will limit applying those original criteria to within the sample and not the outer border region.
Name | Type | Description |
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Fill Holes in Largest Feature | bool | Whether to fill holes within sample after it is identified |
Image
Kind | Default Name | Type | Component Dimensions | Description |
---|---|---|---|---|
Cell Attribute Array | Mask | bool | (1) | Mask array defining what is sample and what is not |
None
Please see the description file distributed with this Plugin
If you need more help with a Filter, please consider asking your question on the DREAM.3D Users Google group!