Slicer3D extension for rating using Likert-type score Deep-learning generated segmentations, with segment editor functionality. Created to speed up the validation process done by a clinician - the dataset loads in one batch with no need to load masks and volumes separately.
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Make window/level and segmentation label toggles persist through cases. #17
Window/level persistence: Added functionality to store and restore window/level settings between cases.
Segmentation label visibility persistence: Implemented storing and restoring of segment visibility states across cases.
Refactored load_nifti_file method: Consolidated duplicate code from load_nifti_file and load_nifti_file_unique into a single method with an optional unique parameter.
Improved scene cleanup: Enhanced node removal process before loading new data to prevent potential conflicts.
Optimized centroid jump functionality: Updated the logic for jumping to segment centroids, now only jumping to visible segments.
Code cleanup: Removed some unused or commented-out code, improving overall readability.
https://github.com/zapaishchykova/SegmentationReview/issues/16