Adversarial prediction of radiotherapy treatment plans

A system for generating one or more radiotherapy treatment plans, the system comprising:

• one or more processors configured to perform operations comprising:
• receiving a set of pairs of image data for each gantry angle of a radiotherapy treatment machine, wherein each pair of the set of pairs comprises a given projection image that represents a view of an anatomy of a subject from a given gantry angle and a given graphical aperture image of multi-leaf collimator (MLC) leaf positions at the given gantry angle based on the given projection image;
• training a generative adversarial network (GAN) model based on the set of pairs of image data for each gantry angle;
• and
• using the trained GAN model to predict an aperture image of MLC leaf positions for a desired gantry angle based on a projection image that represents a view of an anatomical region of interest.

A non-transitory computer-readable medium comprising non-transitory computer-readable instructions for performing operations comprising:

• receiving a set of pairs of image data for each gantry angle of a radiotherapy treatment machine, wherein each pair of the set of pairs comprises a given projection image that represents a view of an anatomy of a subject from a given gantry angle and a given graphical aperture image of multi-leaf collimator (MLC) leaf positions at the given gantry angle based on the given projection image;
• training a generative adversarial network (GAN) model based on the set of pairs of image data for each gantry angle;
• and
• using the trained GAN model to predict an aperture image of MLC leaf positions for a desired gantry angle based on a projection image that represents a view of an anatomical region of interest.