Abstract
Fluid accumulations in between the retinal layers represent one of the main causes of blindness in developed countries. Currently, these fluid accumulations are detected by means of a manual inspection of Optical Coherence Tomography images, prone to subjective and non-quantifiable diagnostics. For this reason, numerous works aimed for an automated methodology. Nonetheless, these systems mostly focus on obtaining a defined segmentation, which is not always possible. For this reason, we present in this work a fully automatic methodology based in a fuzzy and confidence-based visualization of a regional analysis, allowing the clinicians to study the fluid accumulations independently of their distribution, complications and/or other artifacts that may complicate the identification process.
This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research projects and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund - ERDF) and the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016-2019, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. ED431C 2016-047.
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Vidal, P., de Moura, J., Novo, J., Penedo, M.G., Ortega, M. (2020). Intuitive and Coherent Intraretinal Cystoid Map Representation in Optical Coherence Tomography Images. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2019. EUROCAST 2019. Lecture Notes in Computer Science(), vol 12014. Springer, Cham. https://doi.org/10.1007/978-3-030-45096-0_34
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