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A new approach to locate the hippocampus nest in brain MR images

机译:在大脑MR图像中定位海马巢的新方法

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Hippocampal shrinkage is a main biomarker for the detection of Alzheimer's disease and Temporal lobe Epilepsy (TLE). Mostly, developing methods for the hippocampus segmentation are unable to initialize automatically due to its low contrast boundary and uncertain position with respect to the wide range of human brain size. This paper will describe how to reduce the search area in brain MRI to determine the hippocampus location by setting a cuboid slice-based nest for the hippocampus called CSNHC surrounding this structure. The proposed algorithm applies a 3D skull stripping method using BET to extract the brain volume, following by the distance estimation from the first slice that brain volume is seen to the first slice including the hippocampus in the coronal, axial and sagittal views. Finally, ground truths for three different dataset including 68 MR images are used to validate our results.
机译:海马萎缩是检测阿尔茨海默氏病和颞叶癫痫(TLE)的主要生物标志物。通常,海马分割的开发方法由于对比度边界低以及相对于人脑大小范围的不确定位置而无法自动初始化。本文将介绍如何通过围绕海马结构设置一个基于长方体切片的嵌套结构CSNHC来缩小大脑MRI中的搜索区域,从而确定海马结构的位置。所提出的算法应用一种3D头骨剥离方法,使用BET提取大脑体积,然后从在冠状,轴向和矢状视图中可以看到大脑体积的第一个切片到包括海马体的第一个切片的距离估计。最后,使用包括68张MR图像在内的三个不同数据集的真实情况来验证我们的结果。

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