title: Towards automatic quantification of the epicardial fat in non-contrasted CT images.
abstract: In this work, we present a technique to semi-automatically quantify the epicardial fat in non-contrasted computed tomography (CT) images. The epicardial fat is very close to the pericardial fat, being separated only by the pericardium that appears in the image as a very thin line, which is hard to detect. Therefore, an algorithm that uses the anatomy of the heart was developed to detect the pericardium line via control points of the line. From the points detected an interpolation was applied based on the cubic interpolation, which was also improved to avoid incorrect interpolation that occurs when the two variables are non-monotonic. The method is validated by using a set of 40 CT images of the heart of 40 human subjects. In 62.5% of the cases only minimal user intervention was required and the results compared favourably with the results obtained by the manual process.
authors.affiliation: Laboratório de Inteligência Artificial e Ciência dos Computadores, Departamento de Engenharia Informática, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal. jbarbosa@fe.up.pt
authors.forename: Jorge G
authors.initials: JG
authors.lastname: Barbosa
authors.forename: Bruno
authors.initials: B
authors.lastname: Figueiredo
authors.forename: Nuno
authors.initials: N
authors.lastname: Bettencourt
authors.forename: João Manuel R S
authors.initials: JM
authors.lastname: Tavares
mesh_terms: D001331:Automation; D005223:Fats / Q000008:administration & dosage*; D006801:Humans; D010496:Pericardium / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed
chemical_list: D005223:Fats