Papers ECG Digitization
“ECG Digitization” 태그가 달린 논문 9편 · 필터 해제
ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening
Electrocardiography (ECG) is one of the most widely used tests for diagnosing cardiovascular disease. Yet several remote clinics still utilize paper ECG printouts for their analysis due to limited connectivity and comput…
ECG DigitizationImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment
Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly those digitized from ECG images, remain incomplete because of short d…
Multi-Label ClassificationECG DigitizationVLM-in-the-Loop: A Plug-In Quality Assurance Module for ECG Digitization Pipelines
ECG digitization could unlock billions of archived clinical records, yet existing methods collapse on real-world images despite strong benchmark numbers. We introduce \textbf{VLM-in-the-Loop}, a plug-in quality assurance…
ECG DigitizationPTB-XL-Image-17K: A Large-Scale Synthetic ECG Image Dataset with Comprehensive Ground Truth for Deep Learning-Based Digitization
Electrocardiogram (ECG) digitization-converting paper-based or scanned ECG images back into time-series signals-is critical for leveraging decades of legacy clinical data in modern deep learning applications. However, pr…
ECG DigitizationAn Open-Source Python Framework and Synthetic ECG Image Datasets for Digitization, Lead and Lead Name Detection, and Overlapping Signal Segmentation
We introduce an open-source Python framework for generating synthetic ECG image datasets to advance critical deep learning-based tasks in ECG analysis, including ECG digitization, lead region and lead name detection, and…
ECG DigitizationSegmentationWAVIE: A Modular and Open-Source Python Implementation for Fully Automated Digitisation of Paper Electrocardiograms
The electrocardiogram (ECG) is a ubiquitous tool for the assessment of heart disease. While considerable effort has been directed at ECG digitization to facilitate artificial intelligence applications, limitations persis…
ECG Digitizationobject-detectionObject DetectionSegmentation-based Extraction of Key Components from ECG Images: A Framework for Precise Classification and Digitization
The physical and paper Electrocardiography (ECG) contain valuable insights into the history and diversity of cardiovascular diseases (CVDs). The development of algorithms that can digitize and classify these images could…
Deep LearningDiversityECG DigitizationElectrocardiography (ECG)Combining Hough Transform and Deep Learning Approaches to Reconstruct ECG Signals From Printouts
This work presents our team's (SignalSavants) winning contribution to the 2024 George B. Moody PhysioNet Challenge. The Challenge had two goals: reconstruct ECG signals from printouts and classify them for cardiac diseas…
ECG DigitizationECG-Image-Database: A Dataset of ECG Images with Real-World Imaging and Scanning Artifacts; A Foundation for Computerized ECG Image Digitization and Analysis
We introduce the ECG-Image-Database, a large and diverse collection of electrocardiogram (ECG) images generated from ECG time-series data, with real-world scanning, imaging, and physical artifacts. We used ECG-Image-Kit,…
ECG DigitizationTime Series