视觉Transformer架构及其在数字健康中的应用：教程与综述

Vision transformer architecture and applications in digital health: a tutorial and survey.

作者信息

Al-Hammuri Khalid, Gebali Fayez, Kanan Awos, Chelvan Ilamparithi Thirumarai

机构信息

Electrical and Computer Engineering, University of Victoria, Victoria, V8W 2Y2, Canada.

Computer Engineering, Princess Sumaya University for Technology, Amman, 11941, Jordan.

出版信息

Vis Comput Ind Biomed Art. 2023 Jul 10;6(1):14. doi: 10.1186/s42492-023-00140-9.

DOI:10.1186/s42492-023-00140-9

PMID:37428360

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10333157/

Abstract

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.

摘要

视觉Transformer（ViT）是一种用于图像识别任务的先进架构，在数字健康应用中发挥着重要作用。医学图像占数字医学应用中数据的90%。本文讨论了ViT架构的核心基础及其数字健康应用。这些应用包括图像分割、分类、检测、预测、重建、合成以及远程医疗，如报告生成和安全。本文还提出了在数字健康系统中实现ViT的路线图，并讨论了其局限性和挑战。