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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.
Afiliación
  • Besseling RH; Eindhoven University of Technology, the Netherlands. r.m.h.besseling@student.tue.nl
Article en En | MEDLINE | ID: mdl-19964160
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Próstata / Neoplasias de la Próstata / Algoritmos / Reconocimiento de Normas Patrones Automatizadas / Interpretación de Imagen Asistida por Computador / Aumento de la Imagen Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans / Male Idioma: En Revista: Annu Int Conf IEEE Eng Med Biol Soc Año: 2009 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Próstata / Neoplasias de la Próstata / Algoritmos / Reconocimiento de Normas Patrones Automatizadas / Interpretación de Imagen Asistida por Computador / Aumento de la Imagen Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans / Male Idioma: En Revista: Annu Int Conf IEEE Eng Med Biol Soc Año: 2009 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos