Mechouche Ammar, Morandi Xavier, Golbreich Christine, Gibaud Bernard
Unit/Project VisAGeS U746, INSERM/INRIA/CNRS, University of Rennes 1, 35043 Rennes, France.
IEEE Trans Med Imaging. 2009 Aug;28(8):1165-78. doi: 10.1109/TMI.2009.2026746. Epub 2009 Jul 17.
This paper describes an interactive system for the semantic annotation of brain magnetic resonance images. The system uses both a numerical atlas and symbolic knowledge of brain anatomical structures depicted using the Semantic Web standards. This knowledge is combined with graphical data, automatically extracted from the images by imaging tools. The annotations of parts of gyri and sulci, in a region of interest, rely on constraint satisfaction problem solving and description logics inferences. The system is run on a client-server architecture, using Web services and including a sophisticated visualization tool. An evaluation of the system was done using normal (healthy) and pathological cases. The results obtained so far demonstrate that the system produces annotations with high precision and quality.
本文描述了一种用于脑磁共振图像语义标注的交互式系统。该系统同时使用了数字图谱和以语义网标准描述的脑解剖结构的符号知识。这些知识与通过成像工具从图像中自动提取的图形数据相结合。感兴趣区域内脑回和脑沟部分的标注依赖于约束满足问题求解和描述逻辑推理。该系统运行在客户端-服务器架构上，使用网络服务并包括一个复杂的可视化工具。使用正常（健康）和病理病例对该系统进行了评估。目前获得的结果表明，该系统能够产生高精度和高质量的标注。
