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Atlas-registration based image segmentation of MRI human thigh muscles in 3-D space

机译:在3D空间中基于图谱配准的MRI人大腿肌肉图像分割

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Automatic segmentation of anatomic structures of magnetic resonance thigh scans can be a challenging task due to the potential lack of precisely defined muscle boundaries and issues related to intensity inhomogeneity or bias field across an image. In this paper, we demonstrate a combination framework of atlas construction and image registration methods to propagate the desired region of interest (ROI) between atlas image and the targeted MRI thigh scans for quadriceps muscles, femur cortical layer and bone marrow segmentations. The proposed system employs a semi-automatic segmentation method on an initial image in one dataset (from a series of images). The segmented initial image is then used as an atlas image to automate the segmentation of other images in the MRI scans (3-D space). The processes include: ROI labeling, atlas construction and registration, and morphological transform correspondence pixels (in terms of feature and intensity value) between the atlas (template) image and the targeted image based on the prior atlas information and non-rigid image registration methods.
机译:由于潜在缺乏精确定义的肌肉边界以及与整个图像上的强度不均匀性或偏置场有关的问题,磁共振大腿扫描的解剖结构的自动分割可能是一项艰巨的任务。在本文中,我们演示了图集构建和图像配准方法的组合框架,以在图集图像和股四头肌,股骨皮质层和骨髓分割的目标MRI大腿扫描之间传播所需的目标区域(ROI)。所提出的系统对一个数据集中的初始图像(来自一系列图像)采用半自动分割方法。然后,将分割后的初始图像用作图集图像,以自动进行MRI扫描(3-D空间)中其他图像的分割。这些过程包括:ROI标记,图集的构建和配准,以及基于现有图集信息和非刚性图像配准方法的图集(模板)图像和目标图像之间的形态变换对应像素(在特征和强度值方面) 。

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