Image Processing and Error-Correction in DNA via Inpainting and Filtering

Dr. Olgica Milenkovic and Dr. Charles Schroeder at the University of Illinois has developed an error-correction method for DNA-based data storage of massive image datasets.  Previous methods for addressing errors use Reed-Solomon codes at both the individual oligo and pool of oligo level to reconstruct missing strings from redundantly encoded oligos. 

This method uses deep learning techniques to utilize natural redundancy present in the images to perform inpainting on the missing pixels, reconstructing the missing information, and avoiding the requirement for synthesizing and sequencing redundancy in the oligos.