Pith. sign in

REVIEW

Robust reconstruction of cardiac T1 maps using RNNs

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1907.12454 v1 pith:O5GAWYRT submitted 2019-07-29 eess.IV

Nicola Martini , Alessio Vatti , Andrea Ripoli , Sara Salaris , Gianmarco Santini , Maria Filomena Santarelli , Dante Chiappino , Daniele Della Latta This is my paper
classification eess.IV
keywords cardiacmapsreconstructionrobustcomputationalcostfastfitting
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Cardiac magnetic resonance parametric T1 maps are typically reconstructed using non-linear fitting. However this method has limitations due to the high computational cost and robustness. In this study, a recurrent neural network (RNN) is proposed for the robust and fast reconstruction of cardiac T1 maps.

Discussion (0). Sign in to comment.

Pith tools