Fuzzy overlap Jaccard and Dice indices computation #622
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Some details are still to be fixed
| out_file = File("diff.nii", usedefault=True) | ||
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| class FuzzyOverlapOutputSpec(TraitedSpec): |
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some descriptions of each of the outputs needed.
| outputs = self._outputs().get() | ||
| for method in ("dice", "jaccard"): | ||
| outputs[method] = getattr(self, '_' + method) | ||
| #outputs['volume_difference'] = self._volume |
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this looks good, please run pep8 on this file. (in addition to pep8 fixes for this interface, we welcome pep8 fixes on the file if you have time). |
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Added pep8 fixes for the whole interface |
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| >>> overlap = FuzzyOverlap() | ||
| >>> overlap.inputs.in_ref = [ 'ref_class0.nii', 'ref_class1.nii' ] | ||
| >>> overlap.inputs.in_tst = [ 'tst_class0.nii', 'tst_class1.nii' ] |
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you should add those dummy files - otherwise nosetest --with-docetest will fail
Files added in response of #622 (comment)
Minor change, as the names were not descriptive.
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Added dummy files |
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Something else? :) |
chrisgorgo
added a commit
that referenced
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Sep 4, 2013
Fuzzy overlap Jaccard and Dice indices computation
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Calculates various overlap measures between probabilistic distribution maps of segmentations, using the fuzzy definition proposed in: Crum et al., Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis, IEEE Trans. Med. Ima. 25(11),pp 1451-1461, Nov. 2006.
Follows the standard Overlap interface. For justification of this method, please see provided ref.