DIAGNijmegen/ULS23
Repository for the Universal Lesion Segmentation Challenge '23
This project provides a comprehensive dataset of labeled medical images and a baseline model for automatically identifying and outlining various lesions (like tumors, bone lesions) in 3D CT scans. It takes diverse CT imaging data as input and produces precise 3D segmentations of lesions, making it valuable for radiologists and medical researchers who need to accurately locate and measure abnormalities across different body regions.
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Use this if you are a medical professional or researcher working with CT scans and need high-quality, pre-segmented lesion data for training, evaluating, or developing your own medical image analysis tools.
Not ideal if you are looking for a ready-to-use diagnostic tool for patient care without further development or validation.
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Language
Python
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Last pushed
May 11, 2025
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