SEGMENTATION OF UTERINE FIBROID ON MR IMAGES BASED ON CHAN–VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL-Reference-Cited by-同舟云学术

SEGMENTATION OF UTERINE FIBROID ON MR IMAGES BASED ON CHAN–VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL

Published:2014-03-12 Issue:02 Volume:26 Page:1450030
ISSN:1016-2372
Container-title:Biomedical Engineering: Applications, Basis and Communications
language:en
Short-container-title:Biomed. Eng. Appl. Basis Commun.

Author:

Khotanlou Hassan¹,Fallahi Alireza²,Oghabian Mohammad Ali³,Pooyan Mohammad⁴

Affiliation:

1. Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran

2. Department of Biomedical Engineering, Hamedan University of Technology, Hamedan, Iran

3. Research Center for Science and Technology in Medicine, Tehran University of Medical Science, Tehran, Iran

4. Department of Biomedical Engineering, Shahed University, Tehran, Iran

Abstract

Uterine fibroids are common tumors of female pelvis. Uterine artery embolization (UAE) is an effective treatment of symptomatic uterine fibroids by shrinkage of the size of these tumors. Segmentation of the fibroid region is essential for an accurate treatment strategy. Complex fibroids anatomy, nonhomogeneity region and missing boundary in some cases make this task very challenging. In this paper, we present a method to robustly segment these fibroids on magnetic resonance image (MRI). Our method is based on combination of two steps; Chan–Vese level set method and geometric shape prior model. By calculating an initial region inside the fibroid using Chan–Vese level sets method, rough segmentation can be obtained followed by a prior shape model. We found this algorithm efficient, which provides good and reliable result.

Publisher

National Taiwan University

Subject

Biomedical Engineering,Bioengineering,Biophysics

Link

https://www.worldscientific.com/doi/pdf/10.4015/S1016237214500306

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