Table 1.
Layers | Number of neurons in each layer | Activation function | Batch size | Learning rate | Mean Error of estimated T1 (ms) | ||
---|---|---|---|---|---|---|---|
All pixels | Myocardium | Blood | |||||
3 | 400, 400, 1 | Leaky Relu | 64 | 0.01 | 145.5 | -26.7 | 17.9 |
4 | 400, 200, 100, 1 | Leaky Relu | 32 | 0.01 | 145.8 | -22.6 | 9.1 |
5 | 400, 400, 200, 100, 1 | Relu | 64 | 0.01 | 176.5 | 26.2 | 192.8 |
6 | 400, 400, 200, 200, 100, 1 | Leaky Relu | 64 | 0.01 | 111.8 | -9.4 | -7.9 |
7 | 400, 400, 400, 400, 200, 100, 1 | Relu | 64 | 0.001 | 137.6 | 18.1 | 60.2 |
Adam optimizer yields the best result in all experiments. The selected hyperparameters for MyoMapNet are highlighted as bold