Abstract: A method comprises inputting a treatment planning image of a target subject into a machine learning system. The method further comprises determining, by the machine learning system, a first target-subject-specific model of the treatment planning image. The method further comprises applying, by a processing device, the first target-subject-specific model to the treatment planning image to generate a transformed treatment planning image corresponding to a first position of a plurality of positions of the target subject. The method further comprises comparing the transformed treatment planning image to a reference image. The method further comprises, based on the comparing, modifying one or more parameters of the first target-subject-specific model to generate a second target-subject-specific model corresponding to a second position of the plurality of positions.

Abstract: A method including applying a first target-subject-specific model associated with a target subject to a treatment planning image to generate a transformed treatment planning image corresponding to a first position of a plurality of positions. The method also includes modifying one or more hyper-parameters of the first target-subject-specific model to generate a second target-subject-specific model corresponding to a second position of the plurality of positions. The method further includes controlling a radiation treatment delivery device based on the second target-subject-specific model to deliver a radiation treatment to the target subject.

Abstract: A method comprises identifying a treatment planning image of a target subject, the treatment planning image comprising information associated with an arrangement of structures within the target subject. The method further comprises generating, based on the information, a set of reference data associated with the target subject, the reference data indicating a plurality of positions of the target subject. The method further comprises generating target-subject-specific models based on the reference data and modifying one or more hyper-parameters of the target-subject-specific mode to generate second target-subject-specific models corresponding to a second position of the plurality of positions. The method further comprises controlling a radiation treatment delivery device based on the second target-subject-specific model to deliver a radiation treatment to the target subject.

Abstract: A method comprises identifying a treatment planning image of a target subject, the treatment planning image comprising information associated with an arrangement of structures within the target subject. The method further comprises generating, based on the information, a set of reference data associated with the target subject, the reference data indicating a plurality of positions of the target subject. The method further comprises generating target-subject-specific models based on the reference data and modifying one or more hyper-parameters of the target-subject-specific mode to generate second target-subject-specific models corresponding to a second position of the plurality of positions. The method further comprises controlling a radiation treatment delivery device based on the second target-subject-specific model to deliver a radiation treatment to the target subject.

Abstract: A method comprises inputting a treatment planning image of a target subject into a machine learning system. The method further comprises determining, by the machine learning system, a first target-subject-specific model of the treatment planning image. The method further comprises applying, by a processing device, the first target-subject-specific model to the treatment planning image to generate a transformed treatment planning image corresponding to a first position of a plurality of positions of the target subject. The method further comprises comparing the transformed treatment planning image to a reference image. The method further comprises, based on the comparing, modifying one or more parameters of the first target-subject-specific model to generate a second target-subject-specific model corresponding to a second position of the plurality of positions.