Significant changes detection in the follow-up of Retinal Pathologies through computer analysis of Optical Coherence Tomgraphy.

Recently, Optical Coherence Tomograhy (OCT) is widely used to investigate retinal pathologies.Quantitative methods are needed to support qualitative evaluation carried on by medical specialists. Besides retinal thickness measurement, tomographic imaging allows to study macula morphology and tissue structure of retinal cellular layers. Pathological conditions are expected to alter this tissue appearance. Therefore, in the present work, image texture analysis is used to differenziate normal retinas from pathological ones as well as to detect significant changes in follow-up studies. Classical second order statistics, i.e. co-occurrence matrices, and a recent method, known as Local Binary Pattern (LBP), are applied to 25 normal subjects and to 34 patients, affected by vitreo-retinal interface traction syndrome or by retinal edema with various etiology. Both methods have shown a good capability to discriminate between normal and pathoplogical images: a few measured features exhibit signficant differences (p< 0.05) in inner retina, with a strong stability on varying method parameters. Then, a follow-up study was performed: 16 pairs of OCT images of pathological eyes, captured at different times, were selected out of a wider database of consecutive clinical examinations so that they were centered on the fovea, well aligned horizontally and without acquisition artifacts. Details of methods are discussed in the text. Results show a good agreement between clinical findings and the outcomes of co-occurrence, LBP and thickness analysis. Of particular interest is the analysis of critical pixels based on LBP, that allows to follow the pahology evolution in a simple, quantitative way.