Fig. 1: The proposed MaCo framework. | Nature Communications

Fig. 1: The proposed MaCo framework.

From: Enhancing representation in radiography-reports foundation model: a granular alignment algorithm using masked contrastive learning

Fig. 1

a An illustration of the masked contrastive learning strategy employed in MaCo, which leverages the advantages of both contrastive learning and pretext tasks. LR denotes the low-resolution image obtained after downsampling, while HR refers to the original high-resolution image. b The proposed correlation weighting mechanism, (i) shows the basic structure of MaCo, where image and text representations are compared using a contrastive loss, (ii) presents the procedure to generate the importance score, and (iii) plots the method to build correlations.

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