Delta Scan proposes a joint design of scan protocols and image reconstruction to accelerate longitudinal MRI, using image priors from previous exams. The method models the static and dynamic structural information as two adaptive dictionaries, and optimizes sampling patterns using fully-sampled or mildly undersampled historical scans, via a stochastic optimization approach. Extensive experiments show that the proposed method led to improved reconstruction quality under a high acceleration factor, with reduced resolution loss than conventional compressed sensing-based methods. In comparison with previous reference-based reconstruction methods, the proposed method is less overfitted to past exams, truthfully reflecting the anatomical changes between exams.
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