You only need to do segmentation if you want to get quantitative results using Hausdorff or Dice metrics.
It is also useful to do a very simple, threshold-based segmentation if you want to compare two images in a slice view, as it is difficult to see misalignment on two images that are blended together (especially when you want to see small differences), while misalignment is very clearly visible if you overlay extracted contours on an image.
Example 1: perfectly aligned images (left: blending two images; right: overlaying thresholding result on the other image)
Example 2: slightly misaligned images (left: blending two images; right: overlaying thresholding result on the other image). Misalignment appears as slight blurring on the left, and it is clearly visible on the right.
Another common method for quantitative assessment of registration result is to define corresponding anatomical landmarks on the moving and fixed image and compare the position difference between the fixed image landmarks and the transformed moving image landmarks (they should be exactly the same if the registration is perfect). Fiducial registration wizard module (in SlicerIGT extension) can compute this error (and also a transformation) from such anatomical landmarks.