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Automatic Three-Dimensional Segmentation of MR Images Applied to the Rat Uterus

机译:应用于大鼠子宫的MR图像的自动三维分割

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摘要

We introduce an automatic 3D multiscale automatic segmentation algorithm for delineating specific organs in Magnetic Resonance images (MRI). The algorithm can process several modalities simultaneously, and handle both isotropic and anisotropic data in only linear time complexity. It produces a hierarchical decomposition of MRI scans. During this segmentation process a rich set of features describing the segments in terms of intensity, shape and location are calculated, reflecting the formation of the hierarchical decomposition. We show that this method can delineate the entire uterus of the rat abdomen in 3D MR images utilizing a combination of scanning protocols that jointly achieve high contrast between the uterus and other abdominal organs and between inner structures of the rat uterus. Both single and multi-channel automatic segmentation demonstrate high correlation to a manual segmentation. While the focus here is on the rat uterus, the general approach can be applied to recognition in 2D, 3D and multi-channel medical images.
机译:我们介绍了一种自动3D多尺度自动分割算法,用于描绘磁共振图像(MRI)中的特定器官。该算法可以同时处理多个模态,并且仅在线性时间复杂度下处理各向同性和各向异性数据。它会产生MRI扫描的分层分解。在此分割过程中,将计算出一系列根据强度,形状和位置描述分割的特征,这反映了层次分解的形成。我们表明,该方法可以利用扫描协议的组合在3D MR图像中描绘大鼠腹部的整个子宫,共同实现子宫与其他腹部器官之间以及大鼠子宫内部结构之间的高对比度。单通道和多通道自动细分都显示出与手动细分的高度相关性。虽然此处的重点是大鼠子宫,但一般方法可以应用于2D,3D和多通道医学图像的识别。

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