dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
arXiv:1909.10995
Abstract
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.
Presented at ISMRM 27th Annual Meeting & Exhibition (Abstract #658)