A Multiple Geometric Deformable Model Framework for Homeomorphic 3D Medical Image Segmentation.
A Multiple Geometric Deformable Model Framework for Homeomorphic 3D Medical Image Segmentation.
复制标题
用于同构三维医学图像分割的多重几何可变形模型框架。
DOI：
10.1109/cvprw.2008.4563013
复制
发表时间：
2008-07-15
期刊：
影响因子：
--
通讯作者：
Prince JL
中科院分区：
文献类型：
--
作者：
Fan X;Bazin PL;Bogovic J;Bai Y;Prince JL
本文提出了一种用于嵌入水平集的多个对象或舱室的3D分割框架。由于对多个对象的水平集函数的紧凑表示，该框架保证了不重叠和真空，并导致了在很大程度上独立于对象数量的计算高效的进化方案。适当的拓扑约束不仅确保每个对象的拓扑保持不变，而且还确保对象之间的关系保持不变。对象的分解使得该框架对于相关解剖区域的分割或器官的分割特别有吸引力，其中必须保持关系，并且对象界面的不同部分需要不同的进化力。3D全脑分割和丘脑分割的例子证明了我们的方法在这类分割任务中的潜力。
This paper presents a 3D segmentation framework for multiple objects or compartments embedded as level sets. Thanks to a compact representation of the level set functions of multiple objects, the framework guarantees no overlap and vacuum, and leads to a computationally efficient evolution scheme largely independent of the number of objects. Appropriate topology constraints ensure not only that the topology of each object remains the same, but that the relationship between objects is also maintained. The decomposition of objects makes the framework specifically attractive to the segmentation of related anatomical regions or the parcellation of an organ, where relationships must be maintained and different evolution forces are needed on different parts of the objects interface. Examples of 3D whole brain segmentation and thalamic parcellation demonstrate the potential of our method for such segmentation tasks.