Abstract
Optical Coherence Tomography (OCT) has become a relevant image modality in the ophthalmological clinical practice, as it offers a detailed representation of the eye fundus. This medical imaging modality is currently one of the main means of identification and characterization of intraretinal cystoid regions, a crucial task in the diagnosis of exudative macular disease or macular edema, among the main causes of blindness in developed countries. This work presents an exhaustive analysis of intensity and texture-based descriptors for its identification and classification, using a complete set of 510 texture features, three state-of-the-art feature selection strategies, and seven representative classifier strategies. The methodology validation and the analysis were performed using an image dataset of 83 OCT scans. From these images, 1609 samples were extracted from both cystoid and non-cystoid regions. The different tested configurations provided satisfactory results, reaching a mean cross-validation test accuracy of 92.69%. The most promising feature categories identified for the issue were the Gabor filters, the Histogram of Oriented Gradients (HOG), the Gray-Level Run-Length matrix (GLRL), and the Laws’ texture filters (LAWS), being consistently and considerably selected along all feature selector algorithms in the top positions of different relevance rankings.
Highlights
Nowadays, the analysis of different retinal image modalities is a crucial task as part of the diagnosis of many relevant diseases
Using this path as reference, we delimit the search area for other secondary paths. Despite this methodology being able to segment all eight main layers, for this work, we only identified the Inner Limiting Membrane (ILM) and Retinal Pigment Epithelium (RPE)
This size was established after analyzing the performance of the system using progressive window sizes in a preliminary test with representative k Nearest-Neighbors (kNN) and SVM classifiers and a reduced number of features
Summary
The analysis of different retinal image modalities is a crucial task as part of the diagnosis of many relevant diseases. Among the different ophthalmological image modalities, Optical Coherence Tomography (OCT) imaging reached a strong relevance, being widely used by clinicians. It offers a higher detailed representation of the retinal layer tissues, representing in a cross-sectional way the eye fundus and its structures [6]. This technique provides a more complete set of information that outperforms other classical image modalities as can be, for instance, retinographies. Their capture involve a noninvasive and contactless process that is comfortable for both patients and clinicians, making OCT a suitable technique for the analysis of relevant diseases as age-related macular degeneration (AMD) [7], epiretinal membrane [8], or macular edema [9]
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