Technical Program

Paper Detail

Paper:	FR-PM-PS1.11
Session:	Atlas and Model Based Image Segmentation
Time:	Friday, April 7, 13:30 - 14:50
Presentation:	Poster
Title:	A Tightly Coupled Region-Shape Framework for 3D Medical Image Segmentation
Authors:	Rui Huang; Rutgers University
	Vladimir Pavlovic; Rutgers University
	Dimitris Metaxas; Rutgers University
Abstract:	Most hybrid 3D segmentation methods either heuristically couple the respective algorithm or combine a true 3D with a 2D algorithm due to computational considerations. In this paper we propose a new probabilistic framework for 3D image segmentation that combines tightly linked region- and shape-based constraints. Region-based label constraints are modeled by a 3D Markov random field, and are tightly coupled to shape-based constraints of a 3D Deformable Model. The full 3D nature of the combined model leads to a robust smooth surface segmentation that outperforms the single constraint, slice-based as well as the loosely coupled 3D methods.

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