不同切片数的两个体积的图像配准 [英] Image registration of two volume with different number of slices

问题描述

我正在尝试配准来自大脑的两个体积图像(PET 和 CT，甚至 PET 和 MR).这些体积图像中的每一个都包含不同数量的 2D 图像(切片).例如，CT 有 150 个切片，PET 有 100 个切片.我正在考虑使用插值方法计算并将CT切片数量减少到100.这是一种正确的方法吗?有谁知道任何可能对我有帮助的资源?就像一个伪代码，或者我应该通过注册两个体积图像的步骤.谢谢:)

I am trying to register two volumetric images from brain (PET and CT or even PET and MR). Each of these volumetric images contains different numbers of 2D images (slices). For example, CT has 150 slices and PET has 100 slices. I was thinking of using an interpolation method to calculate and reduce the number of CT slices to 100. Is this a correct approach? Does anyone know of any resources that could be helpful for me? like a pseudo code, or steps that I should go through for registering two volumetric images. Thank you :)

推荐答案

如果您知道 150 CT 切片和 100 PET 切片的间距信息，您可以查看 MATLAB 的 interp1 函数，用于沿一个轴插值以将图像重新缩放为相同数量的像素.从这里可以使用 MATLAB 的 imregister 执行注册.

If you know the spacing information for the 150 CT slices and the 100 PET slices, you can look into MATLAB's interp1 function for interpolating along one axis to rescale the images to the same number of pixels. From here it might be possible to use MATLAB's imregister to perform registration.

如果您想了解配准是如何在幕后工作的(在像素和物理坐标之间转换、转换/重新采样图像等)，我可以指导您访问的一个资源是 ITK 软件指南 pdf.

If you are looking to learn how registration works under the hood (transforming between pixel and physical coordinates, transforming/resampling images, etc.), one resource I can direct you to is the ITK Software Guide pdf.

特别是，请尝试阅读关于图像表示的第 1 册第 4.1.4 节(pdf 的第 41 页)和关于变换的第 2 册第 3.9 节(pdf 的第 532 页).

In particular, try reading Book 1 Section 4.1.4 (page 41 of the pdf) on image representation, and Book 2 Section 3.9 (page 532 of the pdf) on transforms.

一般来说，在配准中转换和插入 3D 图像的问题编写代码非常麻烦.您需要问自己像素的间距和方向，如何转换和插值图像以使它们的网格重叠，并且在评估相似性度量时，您还需要决定如何处理网格中位于图像边界之外的像素.

In general, the problem of transforming and interpolating with 3D images in registration can be pretty cumbersome to write code for. You need to ask yourself about the spacing and orientation of pixels, how to transform and interpolate images so that their grids overlap, and you also need to decide what to do with pixels in your grid that lie outside the image boundary when evaluating the similarity metric.

虽然您认为什么是最好的，但我建议您使用现有的注册程序，如果它们能够做您想做的事:

While it's up to you to do what you think is best, I suggest you use existing registration programs if they are capable of doing what you want:

• MATLAB 的 imregister (我从来没有用过，所以我不能评论)
• simpleITK 适用于 Python
• C++ 的 ITK 有一个学习曲线，但可以完全控制注册过程
• elastix 是一个命令行程序，它使用参数的文本文件来执行注册.
• 3D 切片器具有用于简单线性配准的图形用户界面

• MATLAB's imregister (I have never used it so I can't comment on it)
• simpleITK for Python
• the ITK for C++ has a learning curve but gives full control over the registration process
• elastix is a command line program that uses a text file of parameters to perform registration.
• 3D slicer has a graphical user interface for simple linear registration

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