Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images

Despite the limited dataset, we validated ViT with self-attention to learn different types of images to improve recognition accuracy in diagnosing bacterial and fungal keratitis. ViT with self-attention has a meaningful effect on enhancing the diagnostic performance of bacterial and fungal keratitis by combining two or more types of anterior segment images.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2025-03-18
DOI
https://doi.org/10.1016/j.compbiomed.2025.109976
Citations
2
Primary Topic
Ocular Infections and Treatments
Type
article
Field-Weighted Citation Impact
3.41
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article

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images

Yeo Kyoung Won, Jiho Cha, C. Kim, Jooyoung Jeon et al.
2 citations
Computers in Biology and Medicine
Ocular Infections and Treatments
3.41
article

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images

Yeo Kyoung Won, Jiho Cha, C. Kim, Jooyoung Jeon, Dong Hui Lim
article en
2 citations

Abstract

Despite the limited dataset, we validated ViT with self-attention to learn different types of images to improve recognition accuracy in diagnosing bacterial and fungal keratitis. ViT with self-attention has a meaningful effect on enhancing the diagnostic performance of bacterial and fungal keratitis by combining two or more types of anterior segment images.

Computers in Biology and MedicineVol. 190
Korea Advanced Institute of Science and Technology (KR), Samsung Medical Center (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 10%
Ocular Infections and Treatments
3.41
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