Speckle-initialized dynamic segmentation of the prostate

R.M.H. Besseling, S. Zinger, H. Wijkstra, A.J.M. Hendrikx, P.A.J. Hilbers, M. Mischi

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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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
Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2009, 2-6 September 2009. Minneapolis, Minnesota
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages6352-6355
ISBN (Print)978-1-4244-3296-7
DOIs
Publication statusPublished - 2009

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