Automatic modeling and classification of vitreomacular traction pathology stages

Retinal pathologies that are detected too late and/or left untreated can seriously damage eyesight. It is important to monitor the retina and react to any pathological changes. A fast, accurate, non-invasive, and even three-dimensional retina examination is the optical coherence tomography (OCT). In...

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Bibliographic Details
Published in:International Workshops on Image Processing Theory, Tools, and Applications pp. 1 - 6
Main Authors: Stankiewicz, Agnieszka, Marciniak, Tomasz, Dabrowski, Adam, Stopa, Marcin, Rakowicz, Piotr, Marciniak, Elzbieta
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2016
Subjects:
Computational modeling
Distortion
medical image processing
OCT
Pathology
pathology detection
Retina
retina modelling
Shape
Surface topography
Three-dimensional displays
vitreoretinal interface
ISSN:2154-512X
Online Access:Get full text
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Summary:Retinal pathologies that are detected too late and/or left untreated can seriously damage eyesight. It is important to monitor the retina and react to any pathological changes. A fast, accurate, non-invasive, and even three-dimensional retina examination is the optical coherence tomography (OCT). In this paper we propose a new automated classification method for evaluation of vitreomacular interface (VRI) in human eyes. We present an approach for modelling changes in retina structure during the progression of vitreomacular traction (VMT) pathology. Presented experiments were performed on volumetric data acquired from adult patients with the use of Avanti RTvue device. Advanced digital image processing algorithms were subsequently applied to each OCT cross-section (B-scan) for image denoising and flattening, as well as retina layers segmentation. The proposed solution has a good accuracy and almost all subjects were successfully classified into one of 4 groups corresponding to various stages of VMT. The developed models of VMT stages show a high potential of the proposed method to support ophthalmologists in making appropriate clinical decisions.
ISSN:2154-512X
DOI:10.1109/IPTA.2016.7821004