DAGMaN uses co-distilled attention-guided masked image modeling with a noisy teacher to enable effective self-supervised pretraining on medical images by selective masking of co-occurring patches and maintenance of attention head diversity, with demonstrations on nodule classification, immunotherapy
Each nodule was rated on a malignancy from scale 1-5, with ratings of 1−3 as benign and 4−5 as malignant, following the approach of (Chen et al., 2019)
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Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images
DAGMaN uses co-distilled attention-guided masked image modeling with a noisy teacher to enable effective self-supervised pretraining on medical images by selective masking of co-occurring patches and maintenance of attention head diversity, with demonstrations on nodule classification, immunotherapy