Title

Modeling Interaction For Segmentation Of Neighboring Structures

Keywords

Energy minimization; Interaction model; Level set; Neighboring structures; Segmentation; Shape prior

Abstract

This paper presents a new method for segmenting medical images by modeling interaction between neighboring structures. Compared to previously reported methods, the proposed approach enables simultaneous segmentation of multiple neighboring structures for improved robustness. During the segmentation process, the object contour evolution and shape prior estimates are influenced by the interactions between neighboring shapes consisting of attraction, repulsion, and competition. Instead of estimating the a priori shape of each structure independently, an interactive maximum a posteriori shape estimation method is used for estimating the shape priors by considering shape prior distribution, neighboring shapes, and image features. Energy functionals are then formulated to model the interaction and segmentation. With the proposed method, neighboring structures with similar intensities and/or textures, and blurred boundaries can be extracted simultaneously. Experimental results obtained on both synthetic data and medical images demonstrate that the introduced interaction between neighboring structures improves segmentation performance compared with other existing approaches. © 2009 IEEE.

Publication Date

4-3-2009

Publication Title

IEEE Transactions on Information Technology in Biomedicine

Volume

13

Issue

2

Number of Pages

252-262

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TITB.2008.2010492

Socpus ID

63349089194 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/63349089194

This document is currently not available here.

Share

COinS