Mechouche Ammar, Morandi Xavier, Golbreich Christine, Gibaud Bernard
Unit/Project VisAGeS U746, INSERM-INRIA-CNRS-Univ-Rennes 1, France.
Med Image Comput Comput Assist Interv. 2008;11(Pt 1):807-14. doi: 10.1007/978-3-540-85988-8_96.
This paper presents an interactive system for the annotation of brain anatomical structures in Magnetic Resonance Images. The system is based on hybrid knowledge and techniques. First, it exploits both numerical knowledge from atlases and symbolic knowledge from a rule-extended ontology represented in OWL, the Web ontology language, and combines them with graphical data about cortical sulci, automatically extracted from the images. Second, the annotations of the parts of gyri and of sulci located in a region of interest are obtained with different reasoning techniques: Constraint Satisfaction Solving and Description Logics techniques. Preliminary experiments have been achieved on normal and also pathological data. The results obtained so far are very promising.
本文提出了一种用于磁共振图像中脑解剖结构标注的交互式系统。该系统基于混合知识和技术。首先，它利用来自图谱的数值知识以及来自用网络本体语言OWL表示的规则扩展本体的符号知识，并将它们与从图像中自动提取的关于皮质沟的图形数据相结合。其次，使用不同的推理技术来获得位于感兴趣区域的脑回和脑沟部分的标注：约束满足求解和描述逻辑技术。已经在正常和病理数据上进行了初步实验。目前获得的结果非常有前景。
