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首页> 外文会议>International Conference on Electronic Design and Signal processing >Segmentation of Medical Images using Deformable models
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Segmentation of Medical Images using Deformable models

机译：使用可变形模型进行医学图像的分割

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摘要

Deformable models, a promising and vigorously researched model-based approach to computer-assisted medical image analysis. The widely recognized potency of deformable models stems from their ability to segment, match, and track images of anatomic structures by exploiting (bottom-up) constraints derived from the image data together with (top-down) a priori knowledge about the location, size, and shape of these structures. Based on the deformation properties and parameterization the deformable models are categorized in to different types. Here an attempt is made by the author to describe the different types of deformable models with their characterizing properties and their applications to segmentation of medical images.
机译：可变形的模型，有前途和大力研究的基于模型的计算机辅助医学图像分析方法。可变形模型的广泛认可的效力源于它们通过利用从图像数据的（自上而下）的基于位置，大小的先验知识来划分（自下而上）约束来匹配解剖结构的能力，匹配和跟踪解剖结构的图像。和这些结构的形状。基于变形性能和参数化，可变形模型分类为不同类型。这里尝试由作者描述不同类型的可变形模型，其特征属性及其应用于医学图像的分割。

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