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

ABSTRACT

Introduction

Computer vision, understood as the area of science that trains computers to interpret digital images through both artificial intelligence (AI) and classical algorithms, has significantly advanced the analysis and interpretation of optical coherence tomography (OCT) in retina research. The aim of this review is to summarise the recent advances of computer vision in imaging processing in uveitis, with a particular focus in optical coherence tomography images.

Material and Methods

Literature review.

Results

The development of computer vision to assist uveitis diagnosis and prognosis is still undergoing, but important efforts have been made in the field.

Conclusion

The automatising of image processing in uveitis could be fundamental to establish objective and standardised outcomes for future clinical trials. In addition, it could help to better understand the disease and its progression.

KEYWORDS:

• Algorithm
• artificial intelligence
• computer vision
• optical coherence tomography
• uveitis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.