Distributed Markovian segmentation: Application to MR brain scans
Distributed Markovian segmentation: Application to MR brain scans
复制标题
分布式马尔可夫分割：在 MR 脑扫描中的应用
DOI：
10.1016/j.patcog.2007.03.019
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
C. Garbay
中科院分区：
文献类型：
--
作者：
N. Richard;M. Dojat;C. Garbay
提出了一种基于分布式、去中心化和协作策略的马尔可夫图像分割方法。根据这种方法，基于em的模型估计在局部进行，以应对空间变化的强度分布，以及物体外观的非均匀性。这种分布式分割采用协作和分散的策略进行，以保证相邻区域分割的一致性和小样本前模型估计的鲁棒性。需要特定的协调机制来保证对相应处理的适当管理，这些处理在基于响应代理的体系结构的框架中实现。这种方法已经在幻影和真实的1.5T核磁共振脑部扫描上进行了实验。所报道的评价结果表明，该方法特别适用于复杂和空间可变的图像模型。
A situated approach to Markovian image segmentation is proposed based on a distributed, decentralized and cooperative strategy for model estimation. According to this approach, the EM-based model estimation is performed locally to cope with spatially varying intensity distributions, as well as non-homogeneities in the appearance of objects. This distributed segmentation is performed under a collaborative and decentralized strategy, to ensure the consistency of segmentation over neighboring zones, and the robustness of model estimation in front of small samples. Specific coordination mechanisms are required to guarantee the proper management of the corresponding processing, which are implemented in the framework of a reactive agent-based architecture. The approach has been experimented on phantoms and real 1.5T MR brain scans. The reported evaluation results demonstrate that this approach is particularly appropriate in front of complex and spatially variable image models.
影响因子：
19.7
作者：
Kaus, MR;Warfield, SK;Kikinis, R
通讯作者：
Kikinis, R