Adding BI-RADS lesion descriptors as text input to a dual-view iterative attention model raises benign/malignant classification AUC on CBIS-DDSM from 0.711 to 0.872, outperforming a multi-view transformer baseline.
IEEE Transactions on Medical Imaging (2023) 14 G
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Deep BI-RADS Network for Improved Cancer Detection from Mammograms
Adding BI-RADS lesion descriptors as text input to a dual-view iterative attention model raises benign/malignant classification AUC on CBIS-DDSM from 0.711 to 0.872, outperforming a multi-view transformer baseline.