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Automated Meshing of Anatomical Shapes for Deformable Medial Modeling: Application to the Placenta in 3D Ultrasound

机译:可变形内侧建模的自动解剖形状网格划分:在3D超声中用于胎盘的应用

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Deformable medial modeling is an approach to extracting clinically useful features of the morphological skeleton of anatomical structures in medical images. Similar to any deformable modeling technique, it requires a pre-defined model, or synthetic skeleton, of a class of shapes before modeling new instances of that class. The creation of synthetic skeletons often requires manual interaction, and the deformation of the synthetic skeleton to new target geometries is prone to registration errors if not well initialized. This work presents a fully automated method for creating synthetic skeletons (i.e., 3D boundary meshes with medial links) for flat, oblong shapes that are homeomorphic to a sphere. The method rotationally cross-sections the 3D shape, approximates a 2D medial model in each cross-section, and then defines edges between nodes of neighboring slices to create a regularly sampled 3D boundary mesh. In this study, we demonstrate the method on 62 segmentations of placentas in first-trimester 3D ultrasound images and evaluate its compatibility and representational accuracy with an existing deformable modeling method. The method may lead to extraction of new clinically meaningful features of placenta geometry, as well as facilitate other applications of deformable medial modeling in medical image analysis.
机译:可变形的内侧建模是一种提取医学图像中解剖结构的形态骨架的临床有用特征的方法。与任何可变形建模技术相似,它需要在对一类形状的新实例进行建模之前预先定义一类形状的模型或合成骨架。合成骨架的创建通常需要手动交互,并且如果没有很好地初始化,则合成骨架变形为新的目标几何图形很容易产生配准错误。这项工作提出了一种完全自动化的方法,用于为球形的同种圆扁形创建合成骨架(即带有中间链接的3D边界网格)。该方法旋转横截面3D形状,在每个横截面中近似2D中间模型,然后在相邻切片的节点之间定义边以创建规则采样的3D边界网格。在这项研究中,我们演示了在妊娠3D超声图像中对胎盘进行62分割的方法,并使用现有的可变形建模方法评估其兼容性和表示准确性。该方法可导致提取胎盘几何形状的新的临床上有意义的特征,以及促进可变形内侧模型在医学图像分析中的其他应用。

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