Architecture of the MAE for self-supervised pretraining. During pretraining (the top branch), 60% of patches from the input image are masked. The encoder processes the unmasked patches to build a latent representation, which the decoder uses to reconstruct the original image. In the next CME detection stage (the bottom branch), the pretrained encoder generates a latent representation from a full image to support downstream CME localization and segmentation tasks.