Automatic correlation modeling of an internal target

1. An apparatus, comprising:

a data storage device; and

a processing device, operatively coupled to the data storage device, the processing device to:

automatically trigger image acquisition of a plurality of pretreatment images of a target, wherein the plurality of pretreatment images are internal to a patient, wherein acquisition of each of the plurality of pretreatment images is triggered at a different time; and

generate a correlation model distinguishing between inspiration and expiration movements that maps the movements of an external marker to a target location of the target using the plurality of pretreatment images, wherein said automatically triggering comprises automatically triggering image acquisition at substantially evenly-distributed points of a periodic cycle, and wherein said automatically triggering each of the plurality of pretreatment images comprises:

dividing historical data of movement of the target into a plurality of regions based on magnitude of movement of the target;

establishing a plurality of model metric regions using the plurality of regions and inspiration and expiration movement in the historical data, wherein the plurality of model metric regions correspond to a plurality of phases of the periodic cycle;

determining whether a current sample of the target movement is in a desired phase of the periodic cycle by categorizing the current sample into one of the plurality of model metric regions; and

sending an imaging command to an imaging system to acquire the pretreatment image when the current sample is in the desired phase of the periodic cycle.

2. The apparatus of claim 1 , wherein the processing device is to acquire a plurality of data points representative of a corresponding plurality of positions over time of the external marker associated with the patient, wherein the plurality of positions of the external marker define an external path of movement of the external marker, and the external path of movement defines the periodic cycle of the patient.

3. The apparatus of claim 2 , wherein in generating the correlation model, the processing device is to:

identify a path of movement of the target based on the plurality of data points and the plurality of pretreatment images at the substantially evenly-distributed points of the periodic cycle; and

develop the correlation model using the path of movement of the target.

4. The apparatus of claim 1 , wherein the processing device is further to:

derive a target position of the target based on the correlation model;

send a position signal associated with the target position to a beam generator controller; and

control the beam generator controller to direct a beam at the target.

5. The apparatus of claim 1 , wherein the processing device is further to:

periodically generate positional data about the target by automatically acquiring additional images of the target during treatment; and

continuously generate positional data about external motion of the external marker during treatment of the patient.

6. A method, comprising:

automatically triggering, by a processing device, image acquisition of a plurality of pretreatment images of a target, wherein the plurality of pretreatment images are internal to a patient, wherein acquisition of each of the plurality of pretreatment images is triggered at a different time; and

generating, by the processing device, a correlation model distinguishing between inspiration and expiration movements that maps the movements of an external marker to a target location of the target using the plurality of pretreatment images, wherein said automatically triggering comprises automatically triggering image acquisition at substantially evenly-distributed points of a periodic cycle, and wherein said automatically triggering each of the plurality of pretreatment images comprises:

dividing historical data of movement of the target into a plurality of regions based on magnitude of movement of the target;

establishing a plurality of model metric regions using the plurality of regions and inspiration and expiration movement in the historical data, wherein the plurality of model metric regions correspond to a plurality of phases of the periodic cycle;

determining whether a current sample of the target movement is in a desired phase of the periodic cycle by categorizing the current sample into one of the plurality of model metric regions; and

sending an imaging command to an imaging system to acquire the pretreatment image when the current sample is in the desired phase of the periodic cycle.

7. The method of claim 6 , wherein the processing device is to acquire a plurality of data points representative of a corresponding plurality of positions over time of the external marker associated with the patient, wherein the plurality of positions of the external marker define an external path of movement of the external marker, and the external path of movement defines the periodic cycle of the patient.

8. The method of claim 7 , wherein generating the correlation model further comprises:

identifying a path of movement of the target based on the plurality of data points and the plurality of pretreatment images at the substantially evenly-distributed points of the periodic cycle; and

developing the correlation model using the path of movement of the target.

9. The method of claim 6 , further comprising:

deriving a target position of the target based on the correlation model;

sending a position signal associated with the target position to a beam generator controller; and

controlling the beam generator controller to direct a beam at the target.

10. The method of claim 6 , further comprising:

periodically generating positional data about the target by automatically acquiring additional images of the target during treatment; and

continuously generating positional data about external motion of the external marker during treatment of the patient.

11. An apparatus, comprising:

means for automatically triggering image acquisition of a plurality of pretreatment images of a target, wherein the plurality of pretreatment images are internal to a patient, wherein acquisition of each of the plurality of pretreatment images is triggered at a different time; and

means for generating a correlation model distinguishing between inspiration and expiration movements that maps the movements of an external marker to a target location of the target using the plurality of pretreatment images, wherein said automatically triggering comprises automatically triggering image acquisition at substantially evenly-distributed points of a periodic cycle, and wherein said automatically triggering each of the plurality of pretreatment images comprises:

dividing historical data of movement of the target into a plurality of regions based on magnitude of movement of the target;

establishing a plurality of model metric regions using the plurality of regions and inspiration and expiration movement in the historical data, wherein the plurality of model metric regions correspond to a plurality of phases of the periodic cycle;

determining whether a current sample of the target movement is in a desired phase of the periodic cycle by categorizing the current sample into one of the plurality of model metric regions; and

sending an imaging command to an imaging system to acquire the pretreatment image when the current sample is in the desired phase of the periodic cycle.

12. The apparatus of claim 11 , further comprising:

means for acquiring a plurality of data points representative of a corresponding plurality of positions over time of the external marker associated with the patient, wherein the plurality of positions of the external marker define an external path of movement of the external marker, and the external path of movement defines the periodic cycle of the patient.

13. The apparatus of claim 12 , wherein generating the correlation model further comprises:

means for identifying a path of movement of the target based on the plurality of data points and the plurality of pretreatment images at the substantially evenly-distributed points of the periodic cycle; and

means for developing the correlation model using the path of movement of the target.

14. The apparatus of claim 12 , further comprising:

means for deriving a target position of the target based on the correlation model;

means for sending a position signal associated with the target position to a beam generator controller; and

means for controlling the beam generator controller to direct a beam at the target.

15. The apparatus of claim 12 , further comprising:

means for periodically generating positional data about the target by automatically acquiring additional images of the target during treatment; and

means for continuously generating positional data about external motion of the external marker during treatment of the patient.