State-of-the-Art in Retinal Optical Coherence Tomography Image Analysis

TL;DR

This paper reviews recent advances in retinal OCT image analysis, focusing on noise reduction, segmentation, and registration techniques to improve tissue structure interpretation in ophthalmology.

Contribution

It provides a comprehensive overview of current image analysis methods for retinal OCT, highlighting recent developments and challenges in the field.

Findings

Advances in noise reduction improve image clarity.

Segmentation techniques enhance tissue structure delineation.

Registration methods assist in tracking disease progression.

Abstract

Optical Coherence Tomography (OCT) is one of the most emerging imaging modalities that has been used widely in the field of biomedical imaging. From its emergence in 1990's, plenty of hardware and software improvements have been made. Its applications range from ophthalmology to dermatology to coronary imaging etc. Here, the focus is on applications of OCT in ophthalmology and retinal imaging. OCT is able to non-invasively produce cross-sectional volume images of the tissues which are further used for analysis of the tissue structure and its properties. Due to the underlying physics, OCT images usually suffer from a granular pattern, called speckle noise, which restricts the process of interpretation, hence requiring specialized noise reduction techniques to remove the noise while preserving image details. Also, given the fact that OCT images are in the $\mu m$ -level, further analysis in needed to distinguish between the different structures in the imaged volume. Therefore the use of different segmentation techniques are of high importance. The movement of the tissue under imaging or the progression of disease in the tissue also imposes further implications both on the quality and the proper interpretation of the acquired images. Thus, use of image registration techniques can be very helpful. In this work, an overview of such image analysis techniques will be given.