Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Danilo Samuel Jodas (Autor) Outra; Aledir Silveira Pereira (Autor) Outra; João Manuel R. S. Tavares (Autor) FEUP

Ata de Conferência Internacional

Título: European Congress on Computational Methods in Applied Sciences and Engineering: ECCOMAS 2017: VipIMAGE 2017

Páginas: 92-101

6th ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE)

Porto, PORTUGAL, OCT 18-20, 2017

Indexação

ISI Web of Knowledge - 0 Citações

ISI Web of Science

Scopus - 1 Citação

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências da engenharia e tecnologias

Outras Informações

ID Authenticus: P-00N-5X4

DOI: 10.1007/978-3-319-68195-5_10

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10