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Shape Constrained Automatic Segmentation of the Liver based on a Heuristic Intensity Model
 

Summary: Shape Constrained Automatic Segmentation of
the Liver based on a Heuristic Intensity Model
Dagmar Kainm¨uller1
, Thomas Lange2
, and Hans Lamecker1
1
Zuse Institute Berlin, Germany, {kainmueller,lamecker}@zib.de
2
Charit´e Berlin, Germany, thomas.lange@charite.de
Abstract. We present a fully automatic 3D segmentation method for
the liver from contrast-enhanced CT data. It is based on a combination
of a constrained free-form and statistical deformable model. The adap-
tation of the model to the image data is performed according to a simple
model of the typical intensity distribution around the liver boundary and
neighboring anatomical structures, considering the potential presence of
tumors in the liver. All parameters of the deformation as well as the
initial positioning of the model in the data are estimated automatically.
1 Introduction
The main issue in automatic liver segmentation from contrast-enhanced CT
data is that the intensity values of the liver tissue are often similar to those

  

Source: Andrzejak, Artur - Konrad-Zuse-Zentrum für Informationstechnik Berlin

 

Collections: Computer Technologies and Information Sciences