Artificial Intelligence and Imaging Processing in Optical Coherence Tomography and Digital Images in Uveitis

Area of Science:

• Computer vision, encompassing artificial intelligence (AI) and classical algorithms, is revolutionizing digital image interpretation.
• Specifically, it enhances the analysis and interpretation of optical coherence tomography (OCT) images in ophthalmic research.

Background:

• Uveitis diagnosis and prognosis currently face challenges in standardization and objective outcome measures.
• Advancements in computer vision offer potential solutions for objective image processing in uveitis.

Purpose of the Study:

• This review summarizes recent progress in applying computer vision techniques to uveitis imaging.
• The focus is on the processing of optical coherence tomography (OCT) images for uveitis research.

Main Methods:

• A literature review was conducted to identify and synthesize relevant studies.
• The review focused on the application of computer vision in processing OCT images for uveitis.

Main Results:

• Significant efforts have been made in developing computer vision tools for uveitis.
• The field is still evolving, but progress indicates a promising future for AI-assisted diagnosis and prognosis.

Conclusions:

• Automating image processing in uveitis is crucial for establishing objective and standardized outcomes in clinical trials.
• This automation can lead to a better understanding of uveitis and its progression.