Extended Data Fig. 4: Generalization performance evaluation of MedSegX and other competitors on 18 cross-site tasks with different proportions of OOD fine-tuning data (n = 5,801). | Nature Biomedical Engineering

Extended Data Fig. 4: Generalization performance evaluation of MedSegX and other competitors on 18 cross-site tasks with different proportions of OOD fine-tuning data (n = 5,801).

From: A generalist foundation model and database for open-world medical image segmentation

Extended Data Fig. 4: Generalization performance evaluation of MedSegX and other competitors on 18 cross-site tasks with different proportions of OOD fine-tuning data (n = 5,801).

a. 15% fine-tuning data. b. 25% fine-tuning data. c. 50% fine-tuning data. d.100% fine-tuning data. Tasks consist of tooth (X-ray), gallbladder (CT), left kidney (CT), right kidney (CT), left lung (CT), right lung (CT), liver (CT), pancreas (CT), stomach (CT), optic cup (Fundus), optic disc (Fundus), left atrium (MRI), prostate (MRI), right ventricle (MRI), left ventricle (MRI), spleen (MRI), left lung (X-ray), and right lung (X-ray) segmentation. In all box plots, each box shows the quartiles of the distribution, with center as the median, minimum as the first quartile, and maximum as the third quartile. The whiskers extend to the farthest data point that lies within 2× interquartile range (IQR) from the nearest quartile.

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