Hierarchical segmentation of thin structures in volumetric medical images
被引:0
作者:
Holtzman-Gazit, M
论文数: 0引用数: 0
h-index: 0
机构:
Technion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, IsraelTechnion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, Israel
Holtzman-Gazit, M
[1
]
Goldsher, D
论文数: 0引用数: 0
h-index: 0
机构:Technion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, Israel
Goldsher, D
Kimmel, R
论文数: 0引用数: 0
h-index: 0
机构:Technion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, Israel
Kimmel, R
机构:
[1] Technion Israel Inst Technol, Dept Elect Engn, IL-32000 Haifa, Israel
[2] Technion Israel Inst Technol, Fac Med, Rambam Med Ctr, IL-32000 Haifa, Israel
[3] Technion Israel Inst Technol, Fac Med, Dept Comp Sci, IL-32000 Haifa, Israel
来源:
MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2003, PT 2
|
2003年
/
2879卷
关键词:
segmentation;
active surfaces;
energy minimization;
level sets;
variational methods;
PDEs;
D O I:
暂无
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
We introduce a new method for segmentation of 3D medical data based on geometric variational principles. A minimal variance criterion is coupled with a geometric edge alignment measure and the geodesic active surface model. An efficient numerical scheme is proposed. In order to simultaneously detect a number of different objects in the image, a hierarchal method is presented. Finally, our method is compared with the multi-level set approach for segmentation of medical images.