A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis

Heike Hufnagel, Thorsten M. Buzug (Editor)


In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems.
Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.
Original languageEnglish
Place of PublicationWiesbaden
PublisherVieweg+Teubner Verlag
Number of pages147
ISBN (Print)978-3-8348-1722-8
ISBN (Electronic)978-3-8348-8600-2
Publication statusPublished - 19.09.2011

Publication series

NameMedizintechnik - Medizinische Bildgebung, Bildverarbeitung und bildgeführte Interventionen
PublisherVieweg+Teubner Verlag


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