Show simple item record

dc.rights.licensehttps://creativecommons.org/licenses/by-sa/2.5/ar/es_AR
dc.contributor.authorBendersky, Marianaes_AR
dc.contributor.authorIarussi, Emmanueles_AR
dc.contributor.authorDeangeli, Duilioes_AR
dc.contributor.authorPrincich, Juan Pabloes_AR
dc.contributor.authorLarrabide, Ignacioes_AR
dc.contributor.authorOrlando, José Ignacioes_AR
dc.date.accessioned2023-11-16T17:41:06Z
dc.date.available2023-11-16T17:41:06Z
dc.date.issued2023
dc.identifier.urihttps://repositorio.utdt.edu/handle/20.500.13098/12140
dc.description.abstractAlthough normal homologous brain structures are approximately symmetrical by definition, they also have shape differences due to e.g. natural ageing. On the other hand, neurodegenerative conditions induce their own changes in this asymmetry, making them more pronounced or altering their location. Identifying when these alterations are due to a pathological deterioration is still challenging. Current clinical tools rely either on subjective evaluations, basic volume measurements or disease-specific deep learning models. This paper introduces a novel method to learn normal asymmetry patterns in homologous brain structures based on anomaly detection and representation learning. Our framework uses a Siamese architecture to map 3D segmentations of left and right hemispherical sides of a brain structure to a normal asymmetry embedding space, learned using a support vector data description objective. Being trained using healthy samples only, it can quantify deviations-from-normal-asymmetry patterns in unseen samples by measuring the distance of their embeddings to the center of the learned normal space. We demonstrate in public and in-house sets that our method can accurately characterize normal asymmetries and detect pathological alterations due to Alzheimer’s disease and hippocampal sclerosis, even though no diseased cases were accessed for training. Our source code is available at https://github.com/duiliod/DeepNORHAes_AR
dc.format.extent10 p.es_AR
dc.format.mediumapplication/pdfes_AR
dc.languageenges_AR
dc.publisherUniversidad Torcuato Di Tellaes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.subjectNormal Asymmetryes_AR
dc.subjectBrain MRIes_AR
dc.subjectAnomaly detectiones_AR
dc.titleLearning normal asymmetry representations for homologous brain structureses_AR
dc.typeinfo:eu-repo/semantics/preprintes_AR
dc.subject.keywordMachine Learninges_AR
dc.type.versioninfo:eu-repo/semantics/submittedVersiones_AR


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record