DBPF-net: dual-branch structural feature extraction reinforcement network for ocular surface disease image classification

C Wan, Y Mao, W Xi, Z Zhang, J Wang… - Frontiers in Medicine, 2024 - frontiersin.org
Pterygium and subconjunctival hemorrhage are two common types of ocular surface
diseases that can cause distress and anxiety in patients. In this study, 2855 ocular surface …

Research on the automatic classification system of pterygium based on deep learning

K He - International Eye Science, 2022 - pesquisa.bvsalud.org
AIM: To evaluate the application value of the automatic classification and diagnosis system
of pterygium based on deep learning.< p> METHODS: A total of 750 images of normal …

Application of artificial intelligence models for detecting the pterygium that requires surgical treatment based on anterior segment images

F Gan, WY Chen, H Liu, YL Zhong - Frontiers in Neuroscience, 2022 - frontiersin.org
Background and aim A pterygium is a common ocular surface disease, which not only
affects facial appearance but can also grow into the tissue layer, causing astigmatism and …

Pterygium screening and lesion area segmentation based on deep learning

S Zhu, X Fang, Y Qian, K He, M Wu… - Journal of …, 2022 - Wiley Online Library
A two‐category model and a segmentation model of pterygium were proposed to assist
ophthalmologists in establishing the diagnosis of ophthalmic diseases. A total of 367 normal …

[HTML][HTML] Intelligent diagnostic model for pterygium by combining attention mechanism and MobileNetV2

MN Wu, K He, YB Yu, B Zheng, SJ Zhu… - International Journal …, 2024 - ncbi.nlm.nih.gov
METHODS For intelligent diagnosis of pterygium, the attention mechanisms—SENet,
ECANet, CBAM, and Self-Attention—were fused with the lightweight MobileNetV2 model …

Research on an intelligent lightweight‐assisted pterygium diagnosis model based on anterior segment images

B Zheng, Y Liu, K He, M Wu, L Jin, Q Jiang… - Disease …, 2021 - Wiley Online Library
Aims. The lack of primary ophthalmologists in China results in the inability of basic‐level
hospitals to diagnose pterygium patients. To solve this problem, an intelligent‐assisted …

Multi-scale information fusion network with label smoothing strategy for corneal ulcer classification in slit lamp images

L Lv, M Peng, X Wang, Y Wu - Frontiers in Neuroscience, 2022 - frontiersin.org
Corneal ulcer is the most common symptom of corneal disease, which is one of the main
causes of corneal blindness. The accurate classification of corneal ulcer has important …

Automatic classification of colour fundus images for prediction eye disease types based on hybrid features

A Shamsan, EM Senan, HSA Shatnawi - Diagnostics, 2023 - mdpi.com
Early detection of eye diseases is the only solution to receive timely treatment and prevent
blindness. Colour fundus photography (CFP) is an effective fundus examination technique …

[PDF][PDF] Mdcf: Multi-disease classification framework on fundus image using ensemble cnn models

ES Kumar, CS Bindu - Journal of Jilin University, 2021 - osf.io
The purpose of fundus imaging is to examine the anomalies related to diseases that affect
the eye. A fundus image plays a crucial role in the observation and detection of various …

Deep learning for three types of keratitis classification based on confocal microscopy images

X Zhang, G Ding, C Gao, C Li, B Hu, C Zhang… - Proceedings of the …, 2020 - dl.acm.org
Accurate diagnosis of keratitis is important for the follow up treatment. The confocal
microscope can scan different depth and layer of the cornea, therefore is an important tool …