Deep reinforcement learning for computer assisted reading and analysis

A system, comprising:

• an imaging modality configured to generate a first set of patient scan data during a first imaging period;
• and
• a computer configured to:
• receive the patient scan data generated during the first imaging period;
• generate a first reconstructed image by applying a first image model to the patient scan data;
• receive feedback regarding the first reconstructed image;
• provide the feedback as an input to a deep-reinforcement learning process, wherein the deep-reinforcement learning process is configured to generate at least one modification for the first image model based on the feedback regarding the first reconstructed image;
• and
• generate a second image model by applying the at least one modification generated by the deep-reinforcement learning process to the first image model.

A non-transitory computer readable medium storing instructions configured to cause a computer system to execute the steps of:

• receiving, by a system, first patient scan data corresponding to one or more nuclear imaging scans performed on one or more individuals;
• generating, by the system, a first reconstructed image by applying a first image model to the first patient scan data;
• receiving, by the system, feedback regarding the first reconstructed image;
• providing, by the system, the feedback as an input to a deep-reinforcement learning process, wherein the deep-reinforcement learning process is configured to generate at least one modification for the first image model based on the feedback regarding the first reconstructed image;
• and
• generating, by the system, a second image model by applying the at least one modification generated by the deep-reinforcement learning process to the first image model.