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Fig. 5 | Journal of Cardiovascular Magnetic Resonance

Fig. 5

From: Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach

Fig. 5

Phantom T1 maps from two MOLLI sequences (MOLLI5(3)3 and MOLLI4(1)3(1)2) and LL4 with different MyoMapNet models. T1 difference maps between them were included. All MyoMapNet models show similar map quality, except for the model trained using only post-contrast T1 mapping data. In the T1 analysis for the post-contrast models, vials with larger T1 values (> 900 ms) were excluded. While the model trained using only in-vivo data, phantom data show that the model can reliably estimate T1 values for vials with T1/T2s that are not necessarily well represented in the training dataset

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