From Redaction to Restoration: Deep Learning for Medical Image Deidentification and Reconstruction.
This work presents an end-to-end deep learning framework for transforming raw clinical image volumes into de-identified, analysis-ready datasets without compromising downstream utility and automating de-identification and image reconstruction within a single workflow and disseminating large-scale medical imaging collec...