文件通常会被分割成不同大小而且大小是可变的数据块，这样就非常容易导致碎片的存在。

Files are typically divided into fixed-size blocks that are compressed into variable-size blocks, which easily leads into fragmentation.

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传统的基于可变模型的分割方法是一种只基于边界信息的分割方法，就充分利用图像信息的角度来说有其局限性。

Traditional deformable model based segmentation is a method merely based on edge information, which does not make full use of image information.

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在此基础上提出了一种混合区域信息和边界信息的方法——基于融合颜色和强度先验信息的几何可变模型的医学图像分割算法。

Then a new method merging area information and edge information, geometric deformable model with color and intensity priors for medical image segmentation, is proposed.

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