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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.7 no.30 >An efficient method for computing mathematical morphology for medical imaging
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An efficient method for computing mathematical morphology for medical imaging

机译：一种计算医学影像数学形态的有效方法

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摘要

Many medical imaging techniques commonly use mathematical morphology (MM), with flat discs and spheres as the structuring elements (SE). Many efficient methods have been proposed for various types of SE based on the ability to decompose the SE by way of separability or homotopy. Usually, these methods are only able to approximate disc and sphere SE rather than accomplish MM for the exact SE obtained by discretization of such shapes. We present a method for efficiently computing MM on binary and gray scale image volumes using digitally convex and X-Y-Z symmetric flat SE, which includes discs and spheres. The computational cost is a function of the diameter of the SE and rather than its volume. Additional memory overhead is modest. We are able to compute MM on real medical image volumes with greatly reduced running times and increasing gains for larger SE. Our method is also robust to scale: it is applicable to ellipse and ellipsoid SE which may result from discretizing a disc or sphere on an anisotropic grid. Furthermore, it is easy to implement and can make use of existing image comparison operations. We present performance results on medical chest CT datasets.
机译：许多医学成像技术通常使用数学形态学（MM），以圆盘和球体作为结构元素（SE）。基于通过可分离性或同构性分解SE的能力，已经针对各种类型的SE提出了许多有效方法。通常，这些方法仅能够近似圆盘和球体SE，而对于通过离散化此类形状而获得的精确SE则无法完成MM。我们提出了一种使用数字凸面和X-Y-Z对称平面SE（包括磁盘和球体）在二进制和灰度图像体积上有效计算MM的方法。计算成本是SE直径的函数，而不是其体积的函数。额外的内存开销适中。我们能够在实际医学图像上计算MM，并且大大减少了运行时间，并为较大的SE增加了增益。我们的方法在规模上也很健壮：它适用于椭圆形和椭圆形SE，这可能是由于在各向异性网格上离散圆盘或球体而引起的。此外，它易于实现并且可以利用现有的图像比较操作。我们在医疗胸部CT数据集上显示性能结果。

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