Anthony Demolder, Viera Kresnakova, Michal Hojcka, Vladimir Boza, Andrej Iring, Adam Rafajdus, Simon Rovder, Timotej Palus, Martin Herman, Felix Bauer, Viktor Jurasek, Robert Hatala, Jozef Bartunek, Boris Vavrik, Robert Herman
{"title":"利用人工智能实现高精度心电图数字化","authors":"Anthony Demolder, Viera Kresnakova, Michal Hojcka, Vladimir Boza, Andrej Iring, Adam Rafajdus, Simon Rovder, Timotej Palus, Martin Herman, Felix Bauer, Viktor Jurasek, Robert Hatala, Jozef Bartunek, Boris Vavrik, Robert Herman","doi":"10.1101/2024.08.31.24312876","DOIUrl":null,"url":null,"abstract":"<strong>Background</strong> The digitization of electrocardiograms (ECGs) is an important process in modern healthcare, enabling the preservation, transmission, and advanced analysis of ECG data. Traditional methods for digitizing ECGs from paper formats face significant challenges, particularly in real-world scenarios with varying image quality, paper distortions, and overlapping signals. Existing solutions often require manual input and are limited by their dependence on high-quality images and standardized layouts.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High Precision ECG Digitization Using Artificial Intelligence\",\"authors\":\"Anthony Demolder, Viera Kresnakova, Michal Hojcka, Vladimir Boza, Andrej Iring, Adam Rafajdus, Simon Rovder, Timotej Palus, Martin Herman, Felix Bauer, Viktor Jurasek, Robert Hatala, Jozef Bartunek, Boris Vavrik, Robert Herman\",\"doi\":\"10.1101/2024.08.31.24312876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Background</strong> The digitization of electrocardiograms (ECGs) is an important process in modern healthcare, enabling the preservation, transmission, and advanced analysis of ECG data. Traditional methods for digitizing ECGs from paper formats face significant challenges, particularly in real-world scenarios with varying image quality, paper distortions, and overlapping signals. Existing solutions often require manual input and are limited by their dependence on high-quality images and standardized layouts.\",\"PeriodicalId\":501297,\"journal\":{\"name\":\"medRxiv - Cardiovascular Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Cardiovascular Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.08.31.24312876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Cardiovascular Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.31.24312876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High Precision ECG Digitization Using Artificial Intelligence
Background The digitization of electrocardiograms (ECGs) is an important process in modern healthcare, enabling the preservation, transmission, and advanced analysis of ECG data. Traditional methods for digitizing ECGs from paper formats face significant challenges, particularly in real-world scenarios with varying image quality, paper distortions, and overlapping signals. Existing solutions often require manual input and are limited by their dependence on high-quality images and standardized layouts.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
