Affinity registration is possible with the help of examples. In various embodiments the training images is read. An affine transform that is predetermined is used for each of the images used for training. Each affine transform maps the associated image to an image template. Each of the images is assigned an amount of weight. The image that is tested then compared to a weighted combination of the training images. The affine transform is utilized to map the test image to the template. It’s a process of making a weighted mixture of the affine transformed images using the weights.

The present invention relates to affine registers, specifically to example-based, affine register which can be utilized in medical imaging processing.

In accordance with the embodiments of present disclosure, methods of and computer programs for affine registration are offered. A variety of training images can be read in various embodiments. A predetermined affine transformation is read for each of the plurality of training images. Each affine transform maps its associated image to the template. Weights are assigned to every one of the images used for training. The weights are determined to reduce the difference between the test image and a weighted linear mixture of the images used for training. The affine transform is utilized to match the test image onto the template. It’s a weighted mixture of the weights as well as the transformed affine.

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