{"title":"数字健康中的视觉变压器架构和应用:教程和调查。","authors":"Khalid Al-Hammuri, Fayez Gebali, Awos Kanan, Ilamparithi Thirumarai Chelvan","doi":"10.1186/s42492-023-00140-9","DOIUrl":null,"url":null,"abstract":"<p><p>The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that plays an important role in digital health applications. Medical images account for 90% of the data in digital medicine applications. This article discusses the core foundations of the ViT architecture and its digital health applications. These applications include image segmentation, classification, detection, prediction, reconstruction, synthesis, and telehealth such as report generation and security. This article also presents a roadmap for implementing the ViT in digital health systems and discusses its limitations and challenges.</p>","PeriodicalId":52384,"journal":{"name":"Visual Computing for Industry, Biomedicine, and Art","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333157/pdf/","citationCount":"2","resultStr":"{\"title\":\"Vision transformer architecture and applications in digital health: a tutorial and survey.\",\"authors\":\"Khalid Al-Hammuri, Fayez Gebali, Awos Kanan, Ilamparithi Thirumarai Chelvan\",\"doi\":\"10.1186/s42492-023-00140-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that plays an important role in digital health applications. Medical images account for 90% of the data in digital medicine applications. This article discusses the core foundations of the ViT architecture and its digital health applications. These applications include image segmentation, classification, detection, prediction, reconstruction, synthesis, and telehealth such as report generation and security. This article also presents a roadmap for implementing the ViT in digital health systems and discusses its limitations and challenges.</p>\",\"PeriodicalId\":52384,\"journal\":{\"name\":\"Visual Computing for Industry, Biomedicine, and Art\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333157/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Visual Computing for Industry, Biomedicine, and Art\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1186/s42492-023-00140-9\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Visual Computing for Industry, Biomedicine, and Art","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1186/s42492-023-00140-9","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
Vision transformer architecture and applications in digital health: a tutorial and survey.
The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that plays an important role in digital health applications. Medical images account for 90% of the data in digital medicine applications. This article discusses the core foundations of the ViT architecture and its digital health applications. These applications include image segmentation, classification, detection, prediction, reconstruction, synthesis, and telehealth such as report generation and security. This article also presents a roadmap for implementing the ViT in digital health systems and discusses its limitations and challenges.