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

Abstract

We present a fully automatic 3D segmentation method forthe liver from contrast-enhanced CT data. It is based on a combinationof a constrained free-form and statistical deformable model. The adap-tation of the model to the image data is performed according to a simplemodel of the typical intensity distribution around the liver boundary andneighboring anatomical structures, considering the potential presence oftumors in the liver. All parameters of the deformation as well as theinitial positioning of the model in the data are estimated automatically.

Publication
Proc. MICCAI Workshop on 3D Segmentation in the Clinic: A Grand Challenge (T. Heimann at al., eds.), pp. 109-116, 2007

This work won the 2007 MICCAI 3D Segmentation Challenge in the category “Automatic Liver Segmentation” (see results).

Hans Lamecker
Hans Lamecker
Managing Director

Advancing 3D analysis, planning, design and manufacturing using innovative computational methodologies and tools.

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