Share Email Print

Proceedings Paper

3D segmentation of medical volume image using hybrid level set method
Author(s): Myungeun Lee; Wanhyun Cho; Sunworl Kim; Yanjuan Chen; Soohyung Kim
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We present a new segmentation method using the level set framework for the medical volume images. The method has conducted by the curve evolution model based on the geometric variation principle and the level set theory. And the speed function in the level set approach consists of hybrid combination of three integral measures that are derived by the theory of calculus of variation. They are defined by robust alignment term, active region term, and smoothing term. These measures can help to detect the precise location of the target object and prevent from the boundary leakage problem. The proposed method has been tested on the various medical volume images with tumor region to evaluate its performance on visual and quantitative. From the experimental results, an effectiveness and superior performance of our method is relatively excellent compared with traditional approaches.

Paper Details

Date Published: 14 March 2011
PDF: 8 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796235 (14 March 2011); doi: 10.1117/12.877751
Show Author Affiliations
Myungeun Lee, Chonnam National Univ. (Korea, Republic of)
Wanhyun Cho, Chonnam National Univ. (Korea, Republic of)
Sunworl Kim, Chonnam National Univ. (Korea, Republic of)
Yanjuan Chen, Chonnam National Univ. (Korea, Republic of)
Soohyung Kim, Chonnam National Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?