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Hierarchical 3D Shape Model for Segmentation of 4D MR Cardiac Images

机译:用于4D MR心脏图像分割的分层3D形状模型

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摘要

A novel method for the segmentation of 4D MR cardiac images is introduced in this paper. The method improves the traditional active shape model method by adopting an 3D spatially hierarchical expression of the shape model, which is used as an internal regulation force during the segmentation process. Generation of the landmarks for constructing the shape model is based on the active surface method itself utilizing the long range image force, gradient vector flow (GVF). For constructing hierarchical statistical shape models, initial land-marking is done on a manually segmented training set with different spatial resolutions. Principal component analysis is then used to derive the hierarchical expression of the shape model. Experimental results for 4D MR cardiac image segmentation are presented.
机译:介绍了一种新颖的4D MR心脏图像分割方法。该方法通过采用形状模型的3D空间分层表达式来改进传统的主动形状​​模型方法,该表达式在分割过程中用作内部调节力。用于构建形状模型的界标的生成基于主动曲面方法本身,该方法利用了远程图像力,梯度矢量流(GVF)。为了构建分层的统计形状模型,在具有不同空间分辨率的手动分段训练集上进行初始地标标记。然后,使用主成分分析来导出形状模型的层次表达。提出了4D MR心脏图像分割的实验结果。

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