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
相关论文
共 50 条
  • [21] Medical image series segmentation-using watershed transform and active contour model
    Zhu, FP
    Tian, J
    Luo, XP
    Ge, XF
    [J]. 2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 865 - 870
  • [22] An active contour model for medical image segmentation with application to brain CT image
    Qian, Xiaohua
    Wang, Jiahui
    Guo, Shuxu
    Li, Qiang
    [J]. MEDICAL PHYSICS, 2013, 40 (02)
  • [23] A fast pseudo-1D active contour for medical image segmentation
    Sensakovic, W.
    Armato, S.
    Starkey, A.
    [J]. MEDICAL PHYSICS, 2006, 33 (06) : 2196 - 2197
  • [24] A Robust and Fast Active Contour Model for Image Segmentation with Intensity Inhomogeneity
    Ding, Keyan
    Weng, Guirong
    [J]. NINTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2017), 2018, 10615
  • [25] A novel active contour for medical image segmentation
    Saadatmand-Tarjzan, Mahdi
    Ghassemian, Hassan
    [J]. IEICE ELECTRONICS EXPRESS, 2009, 6 (23): : 1683 - 1689
  • [26] Active Contour Model for Image Segmentation
    Zia, Hamza
    Niaz, Asim
    Choi, Kwang Nam
    [J]. 2022 ASIA CONFERENCE ON ADVANCED ROBOTICS, AUTOMATION, AND CONTROL ENGINEERING (ARACE 2022), 2022, : 13 - 17
  • [27] A fast medical image segmentation method of based on initial contour forecast segmentation model
    Peng, Yanjun
    Zhu, Yuxiang
    Wang, Yuanhong
    [J]. INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS, 2016, 7 (03) : 212 - 220
  • [28] Algorithm for segmentation of medical image series based on active contour model
    Luo, Xi-Ping
    Tian, Jie
    Lin, Yao
    [J]. Ruan Jian Xue Bao/Journal of Software, 2002, 13 (06): : 1050 - 1058
  • [29] Accurate and Robust Active Contour Model for Medical Image Segmentation and Correction
    Yang, Yunyun
    Yang, Yunna
    [J]. THIRD INTERNATIONAL SYMPOSIUM ON IMAGE COMPUTING AND DIGITAL MEDICINE (ISICDM 2019), 2019, : 123 - 127
  • [30] Active Contour Model Coupling with Backward Diffusion for Medical Image Segmentation
    Wang, Guodong
    Pan, Zhenkuan
    Zhang, Weizhong
    Dong, Qian
    [J]. PROCEEDINGS OF THE 2013 6TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2013), VOLS 1 AND 2, 2013, : 101 - 105
12345