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Comparison of two methods for the estimation of subcortical volume and asymmetry using magnetic resonance imaging: a methodological study.

机译:两种使用磁共振成像估计皮层下体积和不对称性的方法的比较:方法学研究。

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摘要

The subcortical brain structures are associated with other structures of nervous system; therefore, they have major influence on sensory-motor, limbic and cognitive information processing. Magnetic resonance imaging provides a detailed knowledge of normal and diseased anatomical structures for medical research. The aim of the current study was to compare the volumes of subcortical brain structures and determine the probable volumetric asymmetry in healthy subjects using stereological (point-counting) and semi-automatic segmentation methods.MR scans were obtained from 30 subjects (17 males, 13 females) free of any psychiatric, neurological or cognitive impairment. MR images were analyzed by using stereological (point-counting) and semi-automatic segmentation methods.We did not find any significant differences among the subjects with respect to gender using both methods. This study showed no significant asymmetry in subcortical structures according to methods. Also, no significant difference was found between point-counting and semi-automated segmentation methods for the volumes of subcortical structures (p?>?0.05).From these results, it can be concluded that the semi-automated segmentation method and stereological technique can be used for reliable volume estimation of subcortical structures. However, the stereological method takes less time than semi-automated segmentation; it is simple, reliable and inexpensive. Further studies are required with larger samples in order to support these data.
机译:皮层下的大脑结构与神经系统的其他结构相关。因此,它们对感觉运动,边缘和认知信息处理具有重要影响。磁共振成像为医学研究提供了正常和患病解剖结构的详细知识。本研究的目的是比较健康受试者的皮层下大脑结构的体积,并使用立体(点数)和半自动分割方法确定健康受试者的体积不对称性.MR扫描来自30位受试者(17位男性,13位男性)女性),没有任何精神,神经或认知障碍。 MR图像通过立体(点数)和半自动分割方法进行了分析。我们发现这两种方法在性别方面都没有发现显着差异。这项研究表明,根据方法,皮层下结构没有明显的不对称性。此外,对于皮层下结构的体积,点计数和半自动分割方法之间没有显着差异(p?>?0.05)。从这些结果可以得出结论,半自动分割方法和体视学技术可以用于皮层下结构的可靠体积估计。但是,立体方法比半自动分割所需的时间更少。它简单,可靠且便宜。为了支持这些数据,需要对更大的样本进行进一步的研究。

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