Efficient prealignment of CT scans for registration through a bodypart regressor

H. Meine and A. Hering

in: Medical Imaging with Deep Learning, 2019

Abstract

Convolutional neural networks have not only been applied for classification of voxels, ob-jects, or images, for instance, but have also been proposed as a bodypart regressor. We pickup this underexplored idea and evaluate its value for registration: A CNN is trained to out-put the relative height within the human body in axial CT scans, and the resulting scoresare used for quick alignment between different timepoints. Preliminary results confirm thatthis allows both fast and robust prealignment compared with iterative approaches.

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