Abstract: A computer-implemented method of tissue assessment includes obtaining a plurality of input data samples, each input data sample being representative of tissue in one of multiple views, determining a set of sparse codes for each input data sample of the plurality of input data samples, determining a reconstruction error for the set of sparse codes relative to each dictionary of a set of machine-learned composite dictionaries, and providing the tissue assessment in accordance with the machine-learned composite dictionary in the set of machine-learned composite dictionaries having a minimum reconstruction error of the determined reconstruction errors. Each machine-learned composite dictionary includes a plurality of constituent dictionaries, each constituent dictionary of the plurality of constituent dictionaries being associated with a respective one of the multiple views.

Abstract: A computer-implemented method of tissue assessment includes obtaining a plurality of input data samples, each input data sample being representative of tissue in one of multiple views, determining a set of sparse codes for each input data sample of the plurality of input data samples, determining a reconstruction error for the set of sparse codes relative to each dictionary of a set of machine-learned composite dictionaries, and providing the tissue assessment in accordance with the machine-learned composite dictionary in the set of machine-learned composite dictionaries having a minimum reconstruction error of the determined reconstruction errors. Each machine-learned composite dictionary includes a plurality of constituent dictionaries, each constituent dictionary of the plurality of constituent dictionaries being associated with a respective one of the multiple views.