Segmentation of vertebrae using level sets with expectation maximization algorithm

In this paper, we propose a robust level sets method to segment vertebral bodies (VBs) in clinical computed tomography (CT) images. Since the VB and surrounding organs have very close gray level information and there are no strong edges in some CT images, the initialization of level sets method beco...

Full description

Saved in:
Bibliographic Details
Published in2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro pp. 2010 - 2013
Main Authors Aslan, M S, Farag, A A, Arnold, B, Ping Xiang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2011
Subjects
Biomedical imaging
Bones
Computed tomography
expectation-maximization
Image segmentation
Level set
Robustness
Spine bone
statistical level sets
Three dimensional displays
vertebral body (VB) segmentation
Online AccessGet full text

Cover

More Information
Summary:In this paper, we propose a robust level sets method to segment vertebral bodies (VBs) in clinical computed tomography (CT) images. Since the VB and surrounding organs have very close gray level information and there are no strong edges in some CT images, the initialization of level sets method becomes very crucial step. If the object and background regions are not initialized correctly, the results would not be acceptable. Also, the size and place of the initial seed may give non-reproducible results. To solve these problems, we use a statistical level sets method which uses the Expectation- Maximization (EM) algorithm for the initialization and parameter estimation. Validity was analyzed using ground truths of data sets (expert segmentation) and the European Spine Phantom (ESP) as a known reference. The proposed method is compared with other known alternatives.
ISBN:1424441277
9781424441273
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2011.5872806