Patent ID: 11887221
Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 11:
12. The system of claim 11, wherein iteratively updating the parameter values of the cascaded neural network includes performing an iterative operation including one or more iterations, and each of at least one iteration of the iterative operation includes:
for each of at least some of the plurality of training samples, generating a predicted attenuation-corrected PET image by application of an updated cascaded neural network determined in a previous iteration;
determining, based on the predicted attenuation-corrected PET image and the sample attenuation-corrected PET image of each of the at least some of the plurality of training samples, an assessment result of the updated cascaded neural network; and
further updating the parameter values of the updated cascaded neural network to be used in a next iteration based on the assessment result, wherein during the application of the updated cascaded neural network to a training sample,
each second model of the updated cascaded neural network is configured to receive the sample concatenated image of the training sample and an output image of a previous model that is upstream and connected to the second model in the updated cascaded neural network, and
the predicted attenuation-corrected PET image is an output image of a last second model of the sequentially connected models in the updated cascaded neural network.