A Fast Geodesic Active Contour Model for Medical Image Segmentation Using Prior Analysis and Wavelets

被引：5
|
作者：
Al Sharif, Sharif M. S. [1 ]
Deriche, Mohamed [2 ]
Maalej, Nabil [3 ]
El Ferik, Sami [1 ]
机构：
[1] King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi Arabia
[2] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
[3] King Fahd Univ Petr & Minerals, Dept Phys, Dhahran 31261, Saudi Arabia
来源：
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING | 2014年 / 39卷 / 02期
关键词：
Deformable models; Geometric active contour (GAC); Snake method; Boundary detection; Prior information; Medical image segmentation; INTERPOLATION TECHNIQUE; RECONSTRUCTION; TRACKING; MRI;
D O I：
10.1007/s13369-013-0664-4
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The deformable geodesic active contour (GAC) method is one of the most popular techniques used in object boundary detection in images. In this work, we improve the automatic GAC technique by incorporating prior information extracted from the image region of interest. In addition, we propose a new stopping function to speed up convergence and improve accuracy. The proposed technique was applied to both synthetic and real medical images. The results show both an improvement of more than 40 % in convergence speed together with an excellent accuracy when compared with the previous work.
引用
收藏
页码：1017 / 1037
页数：21
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