Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity

Understand

Non-rigid inter-modality registration can facilitate accurate information fusion from different modalities, but it is challenging due to the very different image appearances across modalities.

• In this paper, we propose to train a non-rigid inter-modality image registration network, which can directly predict the transformation field from the input multimodal images, such as CT and MR images.
• In particular, the training of our inter-modality registration network is supervised by intra-modality similarity metric based on the available paired data, which is derived from a pre-aligned CT and MR dataset.
• Specifically, in the training stage, to register the input CT and MR images, their similarity is evaluated on the warped MR image and the MR image that is paired with the input CT.