Segmentation features needed for intracranial mask computation#46
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Segmentation features needed for intracranial mask computation#46
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…, to be used in intracranial mask computation
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…cientificcomputing/mri-toolkit into cecile/segmentation_refinement
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finsberg
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Apr 23, 2026
…entation.py (as suggested by Henrik)
…Data anymore and have its own from_file function, for the sake of consistency. csf_segmentation is moved to a dedicated CSFSegmentation class
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@finsberg Thanks for all the suggestions. They have been taken into account in the last commits. I have tried to use a smaller portion of the dataset as you did in |
…_refinement Various fixes
…lkit into cecile/segmentation_refinement
finsberg
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Apr 25, 2026
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Looks very good. I still have a few more comments
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| mri: MRIData | ||
| rois: np.ndarray | ||
| lut: pd.DataFrame | ||
| label_name: str |
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I don't understand why we need these lines? We could make Segmentation into a dataclass (in which case we can keep this and possible add a __post_init__ method). Otherwise I think we can remove this.
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| # @dataclass | ||
| class CSFSegmentation: | ||
| segmentation: MRIData |
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I think it is a bit confusing that a segmentation is a MRIData and not a Segmentation.
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…cientificcomputing/mri-toolkit into cecile/segmentation_refinement
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…cientificcomputing/mri-toolkit into cecile/segmentation_refinement
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These functions and the corresponding tests have been added.
The test for segmentation refinement is skipped because it takes quite some time, but I have tested it locally and it reproduces the data from the Gonzo dataset.