A synthetic data pipeline that inserts anatomy-guided shapes and cut-paste objects into chest X-rays trains foreign-object segmentation models to match fully supervised performance with 93 percent fewer manual masks.
The variety of foreign bodies (FB) types complicates dataset creation for detection and segmentation, requiring annotators to identify categories and manage overlapping objects [1]
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Foreign object segmentation in chest x-rays through anatomy-guided shape insertion
A synthetic data pipeline that inserts anatomy-guided shapes and cut-paste objects into chest X-rays trains foreign-object segmentation models to match fully supervised performance with 93 percent fewer manual masks.