Digitizing Paper ECGs at Scale: An Open-Source Algorithm for Clinical Research
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Abstract (arXiv)
Millions of clinical ECGs exist only as paper scans, making them unusable for modern automated diagnostics. We introduce a fully automated, modular framework that converts scanned or photographed ECGs into digital signals, suitable for both clinical and research applications. The framework is validated on 37,191 ECG images with 1,596 collected at Akershus University Hospital, where the algorithm obtains a mean signal-to-noise ratio of 19.65 dB on scanned papers with common artifacts. It is further evaluated on the Emory Paper Digitization ECG Dataset, comprising 35,595 images, including images with perspective distortion, wrinkles, and stains. The model improves on the state-of-the-art in all subcategories. The full software is released as open-source, promoting reproducibility and further development. We hope the software will contribute to unlocking retrospective ECG archives and democratize access to AI-driven diagnostics.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 8 of its 40 references that are in the map. First posted on arXiv 22 Oct 2025.
Builds on
8 of 40 references.
References · 8
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2022Medical Image Segmentation Review: The success of U-Netcited by 191
- 2019Automatic diagnosis of the 12-lead ECG using a deep neural networkcited by 164
- 2023ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram Digitizationcited by 20
- 2020Segmentation Loss Odysseycited by 7
- 2024Combining Hough Transform and Deep Learning Approaches to Reconstruct ECG Signals From Printoutscited by 5
- 2024ECG-Image-Database: A Dataset of ECG Images with Real-World Imaging and Scanning Artifacts; A Foundation for Computerized ECG Image Digitization and Analysiscited by 4
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Citing papers per year: 2026: 3.
3 papers.
- 2026Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMscited by 2
- 2026VLM-in-the-Loop: A Plug-In Quality Assurance Module for ECG Digitization Pipelinescited by 0
- 2026Learning ECG Image Representations via Dual Physiological-Aware Alignmentscited by 0
- 2026Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMs6 Jul 2026
- 2026Learning ECG Image Representations via Dual Physiological-Aware Alignments2 Apr 2026
- 2026VLM-in-the-Loop: A Plug-In Quality Assurance Module for ECG Digitization Pipelines1 Apr 2026