Abstract:Registration of multi-modal medical images is an essential pre-processing step, for example, for fusion or image guided-interventions. However, the alignment process is prone to high variability in tissue appearance between modalities, in addition to local intensity variations and artefacts. This work introduces a robust multi-modal registration approach that mitigates the undesirable effect of such variability. Robustness is achieved using Huber's loss function for the data fidelity and regularization terms. … Show more
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