A self-training teacher-student framework raises pulmonary vessel segmentation precision on COPD CT scans from 88.0% to 90.3% while keeping Dice overlap nearly unchanged.
There are no statistical differences in metric of number of segments, number of endpoints, number of branchpoints, and R (0-1) radius bin across any GOLD grade comparisons
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A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD
A self-training teacher-student framework raises pulmonary vessel segmentation precision on COPD CT scans from 88.0% to 90.3% while keeping Dice overlap nearly unchanged.