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

2014 ◽  
Vol 26 (02) ◽  
pp. 1450030 ◽  
Author(s):  
Hassan Khotanlou ◽  
Alireza Fallahi ◽  
Mohammad Ali Oghabian ◽  
Mohammad Pooyan
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Uterine Fibroids ◽  
Shape Prior ◽  
Mr Images ◽  
Initial Region ◽  
Artery Embolization ◽  
Shape Model ◽  
Prior Model ◽  
Accurate Treatment

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.

Level Set Method Optimized with the Euclidean Distance Transform

2019 ◽  
Author(s):  
Luis Fernando Segalla ◽  
Alexandre Zabot ◽  
Diogo Nardelli Siebert ◽  
Fabiano Wolf
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Euclidean Distance ◽  
Distance Transform ◽  
Euclidean Distance Transform
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