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Reconstruction of Cochlea Based on Micro-CT and Histological Images of the Human Inner Ear

The study of the normal function and pathology of the inner ear has unique difficulties as it is inaccessible during life and, so, conventional techniques of pathologic studies such as biopsy and surgical excision are not feasible, without further impairing function. Mathematical modelling is theref...

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Detalles Bibliográficos
Autores principales: Bellos, Christos, Rigas, George, Spiridon, Ioannis F., Bibas, Athanasios, Iliopoulou, Dimitra, Böhnke, Frank, Koutsouris, Dimitrios, Fotiadis, Dimitrios I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4137506/
https://www.ncbi.nlm.nih.gov/pubmed/25157360
http://dx.doi.org/10.1155/2014/485783
Descripción
Sumario:The study of the normal function and pathology of the inner ear has unique difficulties as it is inaccessible during life and, so, conventional techniques of pathologic studies such as biopsy and surgical excision are not feasible, without further impairing function. Mathematical modelling is therefore particularly attractive as a tool in researching the cochlea and its pathology. The first step towards efficient mathematical modelling is the reconstruction of an accurate three dimensional (3D) model of the cochlea that will be presented in this paper. The high quality of the histological images is being exploited in order to extract several sections of the cochlea that are not visible on the micro-CT (mCT) images (i.e., scala media, spiral ligament, and organ of Corti) as well as other important sections (i.e., basilar membrane, Reissner membrane, scala vestibule, and scala tympani). The reconstructed model is being projected in the centerline of the coiled cochlea, extracted from mCT images, and represented in the 3D space. The reconstruction activities are part of the SIFEM project, which will result in the delivery of an infrastructure, semantically interlinking various tools and libraries (i.e., segmentation, reconstruction, and visualization tools) with the clinical knowledge, which is represented by existing data, towards the delivery of a robust multiscale model of the inner ear.