Abstract: Methods and systems are provided which relate to the planning and delivery of radiation treatments by modalities which involve moving a radiation source along a trajectory relative to a subject while delivering radiation to the subject. An artificial intelligence (AI) agent trained using reinforcement learning (and/or some other suitable form of machine learning) is used to control the radiation delivery parameters in effort to achieve desired delivery of radiation therapy. In some embodiments, the AI agent selects suitable control steps (e.g. radiation delivery parameters for particular time steps), while accounting for patient motions, difference(s) in patient anatomical geometry and/or the like.

Abstract: Methods and systems are provided which relate to the planning and delivery of radiation treatments by modalities which involve moving a radiation source along a trajectory relative to a subject while delivering radiation to the subject. An artificial intelligence (AI) agent trained using reinforcement learning (and/or some other suitable form of machine learning) is used to control the radiation delivery parameters in effort to achieve desired delivery of radiation therapy. In some embodiments, the AI agent selects suitable control steps (e.g. radiation delivery parameters for particular time steps), while accounting for patient motions, difference(s) in patient anatomical geometry and/or the like.

Abstract: A treatment planning apparatus include: a quality metric generator configured to electronically generate a first quality metric based on input received via a user interface; an optimizer configured to determine treatment parameters for a treatment plan that is executable by a processing unit of a treatment machine to operate the treatment machine, wherein the optimizer is configured to determine the treatment parameters for the treatment plan based on the first quality metric; and a controller configured to influence how the optimizer performs optimization, wherein the controller is configured to provide a first continuous function for the first quality metric.

Abstract: Methods and systems are provided which relate to the planning and delivery of radiation treatments by modalities which involve moving a radiation source along a trajectory relative to a subject while delivering radiation to the subject. An artificial intelligence (AI) agent trained using reinforcement learning (and/or some other suitable form of machine learning) is used to control the radiation delivery parameters in effort to achieve desired delivery of radiation therapy. In some embodiments, the AI agent selects suitable control steps (e.g. radiation delivery parameters for particular time steps), while accounting for patient motions, difference(s) in patient anatomical geometry and/or the like.

Abstract: A treatment planning apparatus include: a quality metric generator configured to electronically generate a first quality metric based on input received via a user interface; an optimizer configured to determine treatment parameters for a treatment plan that is executable by a processing unit of a treatment machine to operate the treatment machine, wherein the optimizer is configured to determine the treatment parameters for the treatment plan based on the first quality metric; and a controller configured to influence how the optimizer performs optimization, wherein the controller is configured to provide a first continuous function for the first quality metric.