ECG-DUaL: pose-invariant Digitization of printed electrocardiograms via U-net and Local edge detection

ECG recordings are often stored as paper scans, due to clinical accessibility and tradition.This paper presents a digitization pipeline for ECG printouts based on line detection to correct for rotation, and a U-net for segmentation.The digitization step is differentiable, so the Unet can be fine-tuned for any evaluation metric of interest.The tool achieves a maximum translation-adjusted SNR of 3.047 dB on the George B. Moody PhysioNet Challenge 2024 hidden dataset, placing Ahus AI Lab fourth among the official entries.