Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/107795
Author(s): Danilo Samuel Jodas
Aledir Silveira Pereira
João Manuel R. S. Tavares
Title: Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
Issue Date: 2018
Abstract: The segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images of carotid arteries represents a crucial step towards the evaluation of cerebrovascular diseases. However, the automatic segmentation of the lumen is still a challenge due to the usual low quality of the images and the presence of elements that compromise the accuracy of the results. In this article, we describe a fully automatic method to identify the location of the lumen in MR images of the carotid artery. A circularity index is used to assess the roundness of the regions identified by the K-means algorithm in order to obtain the one with the maximum value, i.e. the potential lumen region. Then, an active contour algorithm is employed to refine the boundary of the region found. The method achieved a maximum Dice coefficient of 0.91 +/- 0.04 and 0.74 +/- 0.16 in 181 postcontrast 3D-T1-weighted and 181 proton density-weighted MR images, respectively. Therefore, the method seems to be promising for identifying the correct location of the lumen in MR images.
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
URI: https://hdl.handle.net/10216/107795
Source: European Congress on Computational Methods in Applied Sciences and Engineering: ECCOMAS 2017: VipIMAGE 2017
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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