NEArBy : Neuroimaging Atlas Based Q/R

• Autor(a) principal: Lemos, João Miguel Palabra
• Data de Publicação: 2013
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/12708
• topic: Engenharia de computadores; Cérebro - Mapeamento; Ressonância magnética; Bancos de dados

Brain atlases have been used as reference to classify and tag topological information either structural or functional from brain images. Using atlases, the resulting analysis allows the extraction of semantic information from the existing image data. However the process of classifying and tagging brain images using an atlas is often tedious and mostly dependent on human observation and validation. At the same time, even when available is often difficult to use, namely when using typical query retrieve services in modern imaging repositories (e.g. DICOM based PACS). In this work we propose NEArBy, a solution that provides query and retrieve services based on brain atlas semantics that can be easily integrated in existing DICOM based imaging repositories. Using a web interface, NEArBy supports not only typical DICOM query retrieve searches but also query tokens matching the brain atlas dictionary. To automate the semantic tagging of the brain images we rely on external methods to identify relevant spatial features that are later labelled using standard brain atlas. Being DICOM a tag based standard, atlases related tags are then privately embedded into DICOM files as NEArBy XML descriptors. These descriptors encode the mapping between feature type, spatial location in the atlas and the respective atlas tag. XML encoded tags are also suitable for indexation by a medical imaging Q/R tool such as Dicoogle allowing queries based both on standard DICOM tags and specifically on atlases related tokens included by NEArBy middleware. NEArBy provides a way to perform queries over a medical imaging repository using technical and atlas based topological information. We illustrate the NEArBy potential usage over a set of functional magnetic resonance imaging (fMRI) datasets using the web user interface to formulate the queries with atlas related criteria and access the retrieved results. Several experiments were successfully performed demonstrating the effectiveness in retrieving subjects with activations in similar areas and in specific locations.