AIMC Topic: Anterior Eye Segment

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Assessing the quality and educational applicability of AI-generated anterior segment images in ophthalmology.

Scientific reports
Text-to-image (T2I) artificial intelligence models are being increasingly explored in medical education, yet their utility in ophthalmology remains unclear. Slit-lamp anterior segment photography, as a cornerstone of ophthalmic training, provides an ...

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Denoising diffusion-based anterior segment optical coherence tomography (AS-OCT) image generation.

International ophthalmology
PURPOSE: This study aims to address the scarcity of annotated Anterior Segment Optical Coherence Tomography (AS-OCT) datasets in ophthalmology by using Denoising Diffusion Generative Adversarial Networks (DD-GANs) to generate synthetic AS-OCT images ...

Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.

Biomedical engineering online
BACKGROUND: Accurate measurement of anterior segment parameters is crucial for diagnosing and managing ophthalmic conditions, such as glaucoma, cataracts, and refractive errors. However, traditional clinical measurement methods are often time-consumi...

Advancements in artificial intelligence for the diagnosis and management of anterior segment diseases.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) in the diagnosis and management of anterior segment diseases has rapidly expanded, demonstrating significant potential to revolutionize clinical practice.

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

Computers in biology and medicine
PURPOSE: To develop three novel Vision Transformer (ViT) frameworks for the specific diagnosis of bacterial and fungal keratitis using different types of anterior segment images and compare their performances.

Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

Scientific reports
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists' diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, in...

Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images.

BMJ open ophthalmology
PURPOSE: To develop an artificial intelligence algorithm to automatically identify the anterior segment structures and assess multiple parameters of primary angle closure disease (PACD) in ultrasound biomicroscopy (UBM) images.

Creating realistic anterior segment optical coherence tomography images using generative adversarial networks.

The British journal of ophthalmology
AIMS: To develop a generative adversarial network (GAN) capable of generating realistic high-resolution anterior segment optical coherence tomography (AS-OCT) images.