Segmentation with Active Contours

被引:4
|
作者
Pierre, Fabien [1 ]
Amendola, Mathieu [1 ]
Bigeard, Clemence [1 ]
Ruel, Timothe [1 ]
Villard, Pierre-Frederic [1 ]
机构
[1] Univ Lorraine, CNRS, INRIA, LORIA, F-54000 Nancy, France
来源
IMAGE PROCESSING ON LINE | 2021年 / 11卷
关键词
active contours; image segmentation; medical imaging; MODELS; SHAPE;
D O I
10.5201/ipol.2021.298
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Active contours (also known as snakes) have shown their ability to introduce regularity on image segmentation. In contrast with level-set approaches, the active contours techniques based on a contour parameterization are able to maintain the initial topology of the area of interest. For this reason, it has been used in recent medical research for diaphragm segmentation. Most of the on-line codes for 2D/3D segmentation, as well as built-in Matlab toolboxes are based on level-set methods. Moreover, in the literature, the implementation details of active contours methods with meshes in three dimensions are tight, making tedious any reproduction of these techniques. In this paper, we give some details of the implementation of active contours in 2D/3D with meshes, especially about the choice of the use of a 2D/3D mesh and its refinement. We also explore the choice of the parameters with a quantitative study of their influence on the segmentation results. The 3D segmentation method has been applied to CT scan images of the lungs.
引用
收藏
页码:120 / 141
页数:22
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