| Autor: |
Khalid Al-hammuri, Fayez Gebali, Awos Kanan, Ilamparithi Thirumarai Chelvan |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Visual Computing for Industry, Biomedicine, and Art, Vol 6, Iss 1, Pp 1-28 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2524-4442 |
| DOI: |
10.1186/s42492-023-00140-9 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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