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Automatic wide-eld registration and mosaicking of noisy OCTA images using template matching and dierential evolution

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dc.contributor.authorMoya García, Alejandro
dc.contributor.directorCarmona Suárez, Enrique Javier
dc.date.accessioned2024-05-20T12:26:18Z
dc.date.available2024-05-20T12:26:18Z
dc.date.issued2020-06
dc.description.abstractOptical Coherence Tomography Angiography (OCTA) is a novel non-invasive ophthalmological technique used to perform a detailed examination of the eye fundus vascularity. However, each of the images obtained by this technique only cover a small retinal area. Thus, ophthalmologists have to take complementary images of the eye fundus from dierent angles in order to obtain a complete visualization of patients' eye fundus. In particular, each set of images must be manually registered by a clinician, being a tedious and time-consuming process. In this work, we propose an approach based on template matching and dierential evolution to automatically register a set of OCTA images characterized by containing noise and artifacts. The proposed method is divided into three main steps. First, a preprocessing step used to extract the main vascular network is applied on every image. Then, an algorithm based on dierential evolution is run on every 2-combination of OCTA images in order to nd the best overlap between them. Finally, a greedy algorithm iteratively selects the best pairs of images (according to their tness) to create the complete mosaic. The proposed method was evaluated via the registration of several sets of OCTA images with the purpose of building their associated mosaics. Results show that our approach is robust and able to achieve a good approximation to the optimal mosaic.en
dc.description.versionversión final
dc.identifier.urihttps://hdl.handle.net/20.500.14468/14247
dc.language.isoen
dc.publisherUniversidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial
dc.relation.centerFacultades y escuelas::E.T.S. de Ingeniería Informática
dc.relation.degreeMáster universitario en Investigación en Inteligencia Artificial
dc.relation.departmentInteligencia Artificial
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject.keywordsOCTA
dc.subject.keywordsretinal imaging
dc.subject.keywordstemplate matching
dc.subject.keywordsdifferential evolution
dc.subject.keywordsmosaicking
dc.titleAutomatic wide-eld registration and mosaicking of noisy OCTA images using template matching and dierential evolutiones
dc.typetesis de maestríaes
dc.typemaster thesisen
dspace.entity.typePublication
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