A shape guided C-V model to segment the levator ani muscle in axial magnetic resonance images

• Tipo: Artigo em Revista Científica Internacional
• Data: 2010

Autores

Zhen Ma (Autor) Outra; Renato Natal M. Jorge (Autor) FEUP; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: Medical Engineering & Physics

Vol. 32 Nº 7

Páginas: 766-774

ISSN: 1350-4533

Editora: Elsevier

Indexação

ISI Web of Knowledge - 33 Citações

ISI Web of Science

Scopus - 40 Citações

INSPEC

COMPENDEX

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Biotecnologia ambiental

CORDIS: Ciências Tecnológicas > Tecnologia > Tecnologia de computadores > Processamento de imagem ; Ciências Tecnológicas > Engenharia > Engenharia biomédica

Outras Informações

ID Authenticus: P-003-3PQ

DOI: 10.1016/j.medengphy.2010.05.002

Abstract (EN): This paper proposes a modified Chan-Vese model to segment levator ani muscles from axial magnetic resonance (MR) images. Intensity variances of the foreground and the background are used as the main segmentation clues. As in most cases the boundary of the rectum can be successfully segmented in axial MR images, it is assumed as a priori and is used to define the region of interest and the initial contour. In order to handle the complex influences of the connective tissues, a shape influence field is formed based on the shape information of the rectum and is integrated into the Chan-Vese model. Several segmentation examples are presented to show the effectiveness of the proposed method and the necessity of adding the shape influences.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9