Patent ID: 11911129
Assignee: SIEMENS HEALTHINEERS AG
Field: Measurement (Instruments)
Classification: CPC A  G | IPC A  G

Claim 22:
23. A training method for manufacturing a deep learning network, the method comprising:
a) providing a deep learning network intended to be trained, the deep learning network configured to output at least one of a probability or a label of a certain cardiac phase at a time from input data;
b) providing multiple training-datasets, based on magnetic resonance imaging (MRI)-k-space measurements of a heart over a measuring-time period and information about a cardiac phase at time points of each training-dataset of the multiple training-datasets;
c) entering a training-dataset of the multiple training datasets into an input layer of the deep learning network;
d) calculating a loss-value based on a difference between the output of the deep learning network and the information about the cardiac phase within a synchronized time;
e) adjusting parameters of the deep learning network;
f) repeating steps d) and e) until the loss-value suits a convergence criterium or a maximum number of repetitions is reached; and
g) repeating steps c) to f) multiple times for different training-datasets.