Optical Coherence Tomography ? Automatic Retina Classification Through Support Vector Machines

Abstract

Optical coherence tomography (OCT) is becoming one of the most important imaging modalities in ophthalmology due to its non-invasiveness and by allowing the visualisation the human retina structure in detail. It was recently proposed that OCT data embeds functional information from the human retina. Specifically, it was proposed that blood-retinal barrier status information is present within OCT data from the human retina. Besides this ability, the authors present data supporting the idea of having the OCT data encoding the ageing of the retina in addition to the disease (diabetes) condition from the healthy status. The methodology followed makes use of a supervised classification procedure, the support vector machine (SVM) classifier -based solely on the statistics of the distribution of OCT data from the human retina (i.e. OCT data between the inner limiting membrane and the retinal pigment epithelium). Results achieved suggest that information on both the healthy status of the blood-retinal barrier and on the ageing process co-exist encoded within the optical properties of the human retina.

Maxwell's equations based 3D model of light scattering in the retina

“…After obtaining the cubature nodes and interpolating the field components to these nodes, the element is re-rotated to its original position. An example is given for N φ (see equations (2) to (4)). The mesh elements are rotated and mapped to the standard triangle defined as I = {r = (r, s)|(r, s) ≥ −1; r + s ≤ 0} from (2) to (3), resulting in the transformation Jacobian J k and integration limit change.…”

“…It is traditionally considered to be composed by ten layers, among which the outer nuclear layer that comprises the cells bodies of light sensitive photoreceptor cells (rods and cones) [1]. Several retinal pathologies, such as diabetic retinopathy, or macular edema, can be detected in their early stages, before noticeable morphologic alterations on the retina [2], by analyzing data acquired through optical coherence tomography (OCT), an imaging technique that uses near infrared light to produce high-resolution images of the retinal tissue [3]. This approach for early diagnosis of retinal conditions is based on functional changes that modify the optical scattering properties of retina, prior to any structural alterations.…”

A Novel Computer-Aided Diagnostic System for Early Detection of Diabetic Retinopathy Using 3D-OCT Higher-Order Spatial Appearance Model

“…They also added demographic data for DR patients and fused it with the features extracted from OCT and OCTA images. Bernardes et al [ 6 ] developed a CAD system using the OCT images to make grading for DR. They used OCT histogram information in their system as a feature extraction from OCT images.…”

Retinal Biomarkers of Alzheimer’s Disease: Insights from Transgenic Mouse Models

“…Our objective is two-fold. On the one hand, we aim to test the classification approach previously applied to OCT data of human retinas to classify those into the healthy control and disease groups [1]. On the other hand, we aim to clarify if changes in the retina are present and can be detected in the early stages of disease.…”