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Space-separated list of label valuess to include. By default, the overlap | Space-separated list of label values to include. By default, the overlap |
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== JSON == |
mri_overlap
This page proposes a new program, called mri_overlap, that will replace the redundant (and buggy/slow) mri_compute_seg_overlap and mri_compute_overlap. A primary new feature is the ability to save a detailed overlap report to a JSON file.
USAGE: mri_overlap <vol1> <vol2> [options] DESCRIPTION: This program computes the overlap between two segmentation volumes. The following statistics can be calculated for each label: dice coefficient - F1-measure of the similarity between the two labels jaccard coefficient - intersecting volume over the combined volume of the two labels volume difference - fractional difference between the label volumes By default, only dice scores are computed, but this can be reconfigured with the --measures flag. Each structure in the input volumes will be considered by default, but an alternative list of labels can be specified with the -l flag. Additionally, the --seg flag will compute the overlap between the following 12 major anatomical structures: Hippocampus (17,53) Caudate (11,50) Putamen (12,51) Pallidum (13,52) Amygdala (18,54) Thalamus Proper (10,49) Lateral Ventricle (4,43) Third and Fourth Ventricles (14,15) Inf Lateral Vent (5,44) Cerebral White Matter (2,41) Cerebral Cortex (3,42) Accumbens Area (26,58) OPTIONAL ARGUMENTS: -o, --out Save detailed overlap report to a JSON file. -m, --measures List of measures to compute. By default, only dice scores are computed. Options include: dice, jaccard, voldiff -l, --labels Space-separated list of label values to include. By default, the overlap will be computed between all labels available in both input volumes. -f, --labelfile File specifying a list of labels to include. This file can either be a space-separated list of label values or in the format of a freesurfer color lookup-table. -s, --seg Compute overlap between the major segmentation structures listed above.
JSON
The proposed JSON output would look something like this:
{ "names": { "1": "structure 1", "2": "structure 2" ... }, "inputs": [ "/path/to/manual_label.mgz", "/other/path/to/aseg.mgz" ], "measures": { "dice": { "mean": 0.9142, "std": 0.0232, "labels": { "2": 0.9143, "3": 0.8739, "4": 0.9002, ... } }, "jaccard": { "mean": 0.8902, "std": 0.0144, "labels": { "2": 0.8921, ... } }, "voldiff": { "mean": 0.0221, "std": 0.0032, "labels": { "2": 0.0123, ... } } } }