A web-based framework for anatomical assessment of the retina using OCT. (October 2015)

• Record Type: Journal Article
• Authors: González-López, Ana; Ortega, Marcos; Penedo, Manuel G.; Charlón, Pablo
• Is Part Of: Biosystems engineering. Volume 138(2015:Oct.)
• Page Start: 44
• Page End: 58
• Publication Date: 2015-10
• Subjects: Medical informatics applications -- Web interface -- Optical coherence tomography (OCT) -- Retinal layers -- Segmentation -- Active contours; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2015.04.001
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Optical Coherence Tomography (OCT) is a clinical standard imaging technique in ophthalmology, which provides much more information than other classical modalities. Since retinal morphology and pathological structures can be identified in an effective way in the OCT images, image processing-based methods are emerging to extract their information. As a prior step to any automatic application for feature extraction, delimitation of retinal layers must be automated. On the other hand, medical research needs to process a large amount of information from different patients and the clinical studies are usually performed in a multi-centre schema. Therefore, not only is automation of retinal layer segmentation needed, but also a flexible framework must be designed to allow the experts to manage all clinical data, as well as extracting features of interest. With that aim, this work presents a framework for OCT image processing, which provides automatic procedures for retinal layer segmentation and the extraction of different statistics for medical-support. A web-based interface was designed in order to make it available to the ophthalmic experts and accessible from different centres. Since the framework was used by ophthalmologists in a real case scenario, its robustness and suitability for this task are shown, making it a very relevant tool for clinical and research purposes. Highlights: Novel web-based framework for retinal analysis in OCT images. Automatic procedures for retinal layer segmentation and extraction of statistics. Multi-stage adaptable active-contour-based process to segment retinal layers. Expert validation shows segmentation equal to or better than state-of-the-art. Framework for experts from multiple centres and evaluated in a real case scenario.