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Automatic delineation of white matter fascicles by localization based upon anatomical spatial relationships

机译:基于解剖空间关系通过定位自动描绘白质束

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Delineation of white matter fascicles is generally achieved with tractography by specifying seeding and exclusion regions of interest (ROIs) defined by anatomical landmarks. In practice, the most popular approach has been to manually draw the ROIs for each scan which requires extensive training, is strongly subject to inter- and intra-expert variability and is highly time consuming. Fully automatic localization of the ROIs is of central interest, particularly for white matter investigations involving a large number of subjects. In this work, we propose an original approach in which the ROIs are localized using the fuzzy set theory by discovering stable anatomical spatial relationships in the brain anatomy. Our approach relies on a learning procedure, in which stable relationships are identified from a limited number of training templates supplied with manually delineated ROIs. For a new subject, the spatial relationships are applied and the ROIs localized. We show that our approach enables successful automatic delineation of the ROIs in the individual. Importantly, we show that this localization is robust across subjects age.
机译:白质束的勾画通常是通过超声检查法来确定的,方法是指定由解剖学界标定义的播种和排斥目标区域(ROI)。在实践中,最流行的方法是为每次扫描手动绘制ROI,这需要大量的培训,并且强烈受专家之间和专家内部的变化的影响,并且非常耗时。 ROI的全自动定位非常重要,特别是对于涉及大量受试者的白质调查而言。在这项工作中,我们提出了一种原始方法,其中通过发现大脑解剖结构中的稳定解剖空间关系,使用模糊集理论对ROI进行了局部化。我们的方法依赖于学习过程,在该过程中,可以从有限数量的培训模板(带有手动描绘的ROI)中识别出稳定的关系。对于新主题,应用空间关系并确定ROI的位置。我们证明了我们的方法能够成功地自动描述个人的投资回报率。重要的是,我们证明了这种本地化在不同年龄段的人中都很强。

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