Clinical Decision Support Tool for the Identification of Pathological Structures Associated with Age-Related Macular Degeneration
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Clinical Decision Support Tool for the Identification of Pathological Structures Associated with Age-Related Macular DegenerationAutor(es)
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2022Cita bibliográfica
Barrientos, I., de Moura, J., Novo, J., Ortega, M., Penedo, M.G. (2022). Clinical Decision Support Tool for the Identification of Pathological Structures Associated with Age-Related Macular Degeneration. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2022. EUROCAST 2022. Lecture Notes in Computer Science, vol 13789. Springer, Cham. https://doi.org/10.1007/978-3-031-25312-6_48
Resumo
[Abstract]: In the field of ophthalmology, different imaging modalities are commonly used to carry out different clinical diagnostic procedures. Currently, both optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A) have made great advances in the study of the posterior pole of the eye and are essential for the diagnosis and monitoring of the treatment of different ocular and systemic diseases. On the other hand, the development of clinical decision support systems is an emerging field, in which clinical and technological advances are allowing clinical specialists to diagnose various pathologies with greater precision, which translates into more appropriate treatment and, consequently, an improvement in the quality of life of patients. This paper presents a clinical decision support tool for the identification of different pathological structures associated with age-related macular degeneration using OCT and OCT-A images. The system provides a useful tool that facilitates clinical decision-making in the diagnosis and treatment of this relevant disease.
Palabras chave
AMD
CAD system
Deep learning
OCT
OCT-A
CAD system
Deep learning
OCT
OCT-A
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18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, Las Palmas de Gran Canaria, 20 - 25 February 2022 This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature's AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-25312-6_48
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