Proper spatial alignment of anatomical landmarks during and between liver imaging exams is challenging due to the dynamic morphology of the liver. Liver-focused registration algorithms have been developed but are typically semiautomatic. We propose a fully-automated pipeline for affine-based registration of inter- and intra-exam liver images and assess performance on clinical liver MRI exams at 1.5T and 3T. The proposed pipeline achieved comparable or superior accuracy and scalability to that reported for previously proposed algorithms. Retrospective image review by an expert abdominal radiologist confirmed subjective improvement in anatomic registration and lesion co-localization. Proof of concept of multimodal scalability was demonstrated.
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