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Speckle-initialized dynamic segmentation of the prostate.
Besseling, R H; Zinger, S; Wijkstra, H; Hendrikx, A M; Hilbers, P A J; Mischi, M.
Afiliação
  • Besseling RH; Eindhoven University of Technology, the Netherlands. r.m.h.besseling@student.tue.nl
Article em En | MEDLINE | ID: mdl-19964160
ABSTRACT
Echography is a commonly used modality for prostate imaging. Prostate segmentation is the first step in analyzing echographic prostate images. Because of the nature of these images, traditional local image processing operators are inadequate for finding the prostate boundary. Most automated segmentations described in literature require user interaction for contour initializing or editing. Also shape templates are applied as prior knowledge. In this paper, an automatic segmentation method is presented, based on prostate specific image granulation and image intensity. First, a granulation detector is used to extract granulation. Subsequently, the Hessian is adopted to evaluate granulation shape and intensity for the extraction of the prostate-specific dot pattern. This dot pattern is used to construct the contour initialization. A smooth contour model (discrete dynamic contour; DDC) is evolved from this initialization to the final contour. The guiding vector field for the DDC deformation is the gradient vector flow field calculated from an edge map of the original image. The scale of the relevant edges (large compared to granulation) is estimated from the prostate-specific dot pattern. Comparison of automated segmentations with clinical expert manual segmentations reveals a mean sensitivity and accuracy of 0.90 and 0.93, respectively.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próstata / Neoplasias da Próstata / Algoritmos / Reconhecimento Automatizado de Padrão / Interpretação de Imagem Assistida por Computador / Aumento da Imagem Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Humans / Male Idioma: En Revista: Annu Int Conf IEEE Eng Med Biol Soc Ano de publicação: 2009 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próstata / Neoplasias da Próstata / Algoritmos / Reconhecimento Automatizado de Padrão / Interpretação de Imagem Assistida por Computador / Aumento da Imagem Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Humans / Male Idioma: En Revista: Annu Int Conf IEEE Eng Med Biol Soc Ano de publicação: 2009 Tipo de documento: Article País de afiliação: Holanda