AIMC Topic: Cornea
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An optimized multi-scale dilated attention layer for keratoconus disease classification.
International ophthalmology
Jul 30, 2025
INTRODUCTION: Keratoconus (KCN) is a progressive and non-inflammatory corneal disorder characterized by thinning and conical deformation of the cornea, resulting in visual impairment. Early and accurate detection is crucial to prevent disease progres...
Characterising corneal changes in aniridia-related keratopathy using in vivo confocal microscopy and a self-supervised AI model.
BMJ open ophthalmology
Jul 16, 2025
PURPOSE: To investigate whether corneal changes observed via in vivo confocal microscopy (IVCM) in patients with aniridia-related keratopathy (ARK) reflect clinical severity.
Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data.
Scientific reports
Jul 8, 2025
Keratoconus is a progressive eye disease characterized by the thinning and bulging of the cornea, leading to visual impairment. Early and accurate diagnosis is crucial for effective management and treatment. This study investigates the application of...
Artificial intelligence derived grading of mustard gas induced corneal injury and opacity.
Scientific reports
Jul 1, 2025
Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessing corneal damage due to chemical injury in live rabbits remains lacking. This study aimed to develo...
Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.
Computer methods and programs in biomedicine
Apr 28, 2025
OBJECTIVE: Artificial intelligence (AI) models are effective for analyzing high-quality slit-lamp images but often face challenges in real-world clinical settings due to image variability. This study aims to develop and evaluate a hybrid AI-based ima...
Using 3D Convolutional Neural Network and Corvis ST Corneal Dynamic Video for Detecting Forme Fruste Keratoconus.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Apr 1, 2025
PURPOSE: To evaluate the performance of a three-dimensional convolutional neural network (3D CNN) in detecting forme fruste keratoconus (FFKC).
Advances in machine learning for keratoconus diagnosis.
International ophthalmology
Mar 30, 2025
PURPOSE: To review studies reporting the role of Machine Learning (ML) techniques in the diagnosis of keratoconus (KC) over the past decade, shedding light on recent developments while also highlighting the existing gaps between academic research and...
A lightweight PCT-Net for segmenting neural fibers in low-quality CCM images.
Computers in biology and medicine
Mar 22, 2025
In this paper, we propose a lightweight Position Channel Transformer Network (PCT-Net) for segmenting slender neural fibers in low-quality corneal confocal microscopy images with speckle noise and uneven lighting. Three modules including the channel ...
Hybrid data augmentation strategies for robust deep learning classification of corneal topographic maptopographic map.
Biomedical physics & engineering express
Jan 30, 2025
Deep learning has emerged as a powerful tool in medical imaging, particularly for corneal topographic map classification. However, the scarcity of labeled data poses a significant challenge to achieving robust performance. This study investigates the...
The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading.
Scientific reports
Jan 9, 2025
We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims to investigate the influence of AI's misleading guidance on ophthalmologists' responses. This cross...
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