Use Cases
MONAI-label has mainly three use cases:
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Cold-start annotation: The user can annotate a dataset from scratch using basic viewer capabilities (i.e. brushes, DeepGrow)
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Interactive label editing or modification: The user can modify or edit annotations created by an automatic model.
- Model quality improvement: This is designed to take advantage of an expert budget (i.e. 5 hours per week of a radiologist) to improve the quality of a segmentation model. For this, there are several active learning techniques and base learner models that allow this to happen.
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DeepGrow App Based Use Case to Speed up Annotation Time: The below table shows how the annotation time at the user's end can be reduced as more and more volumes are annotated.
