scalability and enhance performance
dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
Schlemper, Jo, Oksuz, Ilkay, Clough, James R., Duan, Jinming, King, Andrew P., Schnabel, Julia A., Hajnal, Joseph V., Rueckert, Daniel
AUTOMAP is a promising generalized reconstruction approach, however, it is not scalable and hence the practicality is limited. We present dAUTOMAP, a novel way for decomposing the domain transformation of AUTOMAP, making the model scale linearly. We show dAUTOMAP outperforms AUTOMAP with significantly fewer parameters.