Extended Data Fig. 6: Feature similarity analysis between various pre-trained backbone projections. | Nature Biomedical Engineering

Extended Data Fig. 6: Feature similarity analysis between various pre-trained backbone projections.

From: Accurate prediction of disease-risk factors from volumetric medical scans by a deep vision model pre-trained with 2D scans

Extended Data Fig. 6

Shown are nine scatterplots of similarity analysis (CKA) when comparing the projections of a biomedical-imaging dataset induced by different biomedical-imaging pre-trained backbones. Each panel corresponds to a different pair of pre-trained backbones (upper- biomedical pairs; middle- biomedical and ImageNet pairs; lower- biomedical and random pairs). In each panel, each of the 768 dots represents the similarity score computed for the projections induced by the corresponding filter. A dot is red if it falls within the top 5% scores (and gray otherwise). The dashed lines show the average score measured for the color-corresponding set of dots.

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