Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
J Biomed Inform. 2012 Jun;45(3):522-7. doi: 10.1016/j.jbi.2012.02.013. Epub 2012 Apr 3.
A method for automated location of shape differences in diseased anatomical structures via high resolution biomedical atlases annotated with labels from formal ontologies is described. In particular, a high resolution magnetic resonance image of the myocardium of the human left ventricle was segmented and annotated with structural terms from an extracted subset of the Foundational Model of Anatomy ontology. The atlas was registered to the end systole template of a previous study of left ventricular remodeling in cardiomyopathy using a diffeomorphic registration algorithm. The previous study used thresholding and visual inspection to locate a region of statistical significance which distinguished patients with ischemic cardiomyopathy from those with nonischemic cardiomyopathy. Using semantic technologies and the deformed annotated atlas, this location was more precisely found. Although this study used only a cardiac atlas, it provides a proof-of-concept that ontologically labeled biomedical atlases of any anatomical structure can be used to automate location-based inferences.
通过带有正式本体论标签注释的高分辨率生物医学图谱，描述了一种用于自动定位病变解剖结构中形状差异的方法。具体来说，对人类左心室的高分辨率磁共振图像进行了分割，并使用从解剖学基础模型本体论的一个提取子集提取的结构术语进行了注释。使用变形配准算法，将图谱注册到先前心肌病左心室重构研究的心动末期模板。先前的研究使用阈值和目视检查来定位一个具有统计学意义的区域，该区域可区分缺血性心肌病患者和非缺血性心肌病患者。使用语义技术和变形注释图谱，可以更精确地找到该位置。尽管这项研究仅使用了心脏图谱，但它提供了一个概念验证，即任何解剖结构的本体论标记的生物医学图谱都可以用于自动化基于位置的推理。
