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Perturbing the Initial Registration

In order to perform a systematic evaluation of the effects of misregistration, we created multiple image sets, based on the MGH Dataset, but with controlled degrees of misregistration. To create a misregistered set, we took the original image set and applied a set of smooth pseudo-random spatial warps, based on biharmonic Clamped Plate Splines [20]. The warp for each image was controlled by 25 randomly placed knot-points, each displaced in a random direction by a distance drawn from a Gaussian distribution whose mean controlled the degree of misregistration introduced. This provided a very general family of warps. We summarised the degree of misregistration by measuring 79#79, the average magnitude of pixel displacement over the whole image. We generated a total of 70 misregistered image sets - 10 warp-set instantiations for each of 7 different values of 79#79 (0.0643, 0.249, 0.685, 1.36, 2.21, 2.76, and 4.15 pixels). Examples of warped images are shown in Figure .

Figure: An example affinely-aligned brain image and its accompanying anatomical labels, both overlaid and expanded, for gray matter, white matter, the lateral ventricles, and the caudate nucleus. The labels are also divided into left and right.

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Figure: An original image from the MGH Dataset (top left) and examples of warped versions of the same image obtained using different values of 79#79, the mean pixel displacement (shown on each image).

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