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Aligning Slices Automatically

A number of matching processes, including Feature Based, Mutual Information, SSD (sum of squared differences), and Template Matching, are available for aligning slices automatically (see Registration and Compensation Methods). You should note that methods to quantify the degree of similarity between images, and apply the required linear transformations to register 2D slices within the 3D image stack, are based on different concepts and that results may differ significantly. The performance of each algorithm is also dependent on the input data and the settings selected for registration. You may find that selecting an appropriate matching process for you data is often best done by trial and error.

Although it is not possible to recommend which matching method will provide the best results for your data or what slice alignment workflow should be used, you should consider the following before you attempt to align slices automatically:

Transformations can be implemented by either one of two mechanisms — at the input so that the original image data is transformed, or at the output so that a new dataset is created and the original image remains unmodified.

 

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