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An automatic method for colon segmentation in CT colonography.
Bert, Alberto; Dmitriev, Ivan; Agliozzo, Silvano; Pietrosemoli, Natalia; Mandelkern, Mark; Gallo, Teresa; Regge, Daniele.
Afiliação
  • Bert A; im3D S.p.A. Medical Imaging Lab, Via Lessolo 3, 10153 Torino, Italy. alberto.bert@i-m3d.com
Comput Med Imaging Graph ; 33(4): 325-31, 2009 Jun.
Article em En | MEDLINE | ID: mdl-19304454
ABSTRACT
An automatic method for the segmentation of the colonic wall is proposed for abdominal computed tomography (CT) of the cleansed and air-inflated colon. This multistage approach uses an adaptive 3D region-growing algorithm, with a self-adjusting growing condition depending on local variations of the intensity at the air-tissue boundary. The method was evaluated using retrospectively collected CT scans based on visual segmentation of the colon by expert radiologists. This evaluation showed that the procedure identifies 97% of the colon segments, representing 99.8% of the colon surface, and accurately replicates the anatomical profile of the colonic wall. The parameter settings and performance of the method are relatively independent of the scanner and acquisition conditions. The method is intended for application to the computer-aided detection of polyps in CT colonography.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Reconhecimento Automatizado de Padrão / Inteligência Artificial / Interpretação de Imagem Assistida por Computador / Colo / Imageamento Tridimensional / Colonografia Tomográfica Computadorizada Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2009 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Reconhecimento Automatizado de Padrão / Inteligência Artificial / Interpretação de Imagem Assistida por Computador / Colo / Imageamento Tridimensional / Colonografia Tomográfica Computadorizada Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2009 Tipo de documento: Article