A method for determining a radiation treatment plan includes defining a part of a treatment using control points, defining dose calculation points, calculating dose in the dose calculation points, and changing a number of the dose calculation points. A method for determining a radiation treatment pl
A method for determining a radiation treatment plan includes defining a part of a treatment using control points, defining dose calculation points, calculating dose in the dose calculation points, and changing a number of the dose calculation points. A method for determining a radiation treatment plan includes modeling a first part of a treatment plan using a fluence map, and modeling a second part of the treatment plan using a first machine parameter. A method for determining a radiation treatment plan includes determining a plurality of dose calculation points, determining a level of complexity of fluence for one of the plurality of dose calculation points, and converting a fluence map to one or more machine parameters for the one of the plurality of dose calculation points based on the determined level of complexity.
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What is claimed is: 1. A method for determining a radiation treatment plan, comprising: defining a part of a treatment using control points; defining dose calculation points, wherein a first total number of the dose calculation points is fewer than a second total number of the control points; calcu
What is claimed is: 1. A method for determining a radiation treatment plan, comprising: defining a part of a treatment using control points; defining dose calculation points, wherein a first total number of the dose calculation points is fewer than a second total number of the control points; calculating dose for the dose calculation points using a processor; changing the first total number of the dose calculation points; using the changed first total number of the dose calculation points to determine a treatment plan; and storing the treatment plan in a computer-readable medium. 2. The method of claim 1, further comprising changing the second total number of the control points. 3. The method of claim 1, wherein the act of defining the part of the treatment using the control points comprises determining one or more machine parameters. 4. The method of claim 3, wherein the one or more machine parameters are selected from the group consisting of leaf sequence, collimator position, gantry rotation speed, gantry position, couch position, beam activation signal, beam deactivation signal, dose, dose rate, beam energy, and beam type. 5. The method of claim 1, wherein an optimization technique is used to change the first total number of the dose calculation points. 6. The method of claim 5, wherein the optimization technique is iterative. 7. The method of claim 6, wherein the first total number of the dose calculation points is changed in one iteration. 8. The method of claim 1, wherein ranges of the control points comprise different maximum speed of gantry rotation. 9. The method of claim 1, wherein the dose calculation points correspond with respective gantry ranges. 10. The method of claim 1, wherein the dose calculation points correspond with respective time periods. 11. The method of claim 1, wherein the dose calculation points correspond with respective monitor units. 12. The method of claim 1, wherein the dose calculation points correspond with respective regions of a patient, respective collimator angles, respective couch positions, or respective couch angles. 13. A computer product having a set of instructions stored in a computer-readable medium, an execution of which causes a process to be performed, the process comprising: providing a user interface for allowing a user to define a part of a treatment using control points, and for allowing the user to define dose calculation points; calculating dose for the dose calculation points, wherein a first total number of the dose calculation points is fewer than a second total number of the control points; and changing the first total number of the dose calculation points; using the changed first total number of the dose calculation points to determine a radiation treatment plan; and storing said treatment plan in a computer. 14. The computer product of claim 13, wherein the process further comprises changing the second total number of the control points. 15. The computer product of claim 13, wherein the act of defining the part of the treatment using the control points comprises determining one or more machine parameters. 16. The computer product of claim 15, wherein the one or more machine parameters are selected from the group consisting of leaf sequence, collimator position, gantry rotation speed, gantry position, couch position, beam activation signal, beam deactivation signal, dose, dose rate, beam energy, and beam type. 17. The computer product of claim 13, wherein an optimization technique is used to change the first total number of the dose calculation points. 18. The computer product of claim 17, wherein the optimization technique is iterative. 19. The computer product of claim 18, wherein the first total number of the dose calculation points is changed in one iteration. 20. The computer product of claim 13, wherein ranges of the control points comprise different maximum speed of gantry rotation. 21. The computer product of claim 13, wherein the computer product comprises a processor for performing the acts of providing, calculating, and changing. 22. The computer product of claim 13, wherein the dose calculation points correspond with respective gantry ranges. 23. The computer product of claim 13, wherein the dose calculation points correspond with respective time periods. 24. The computer product of claim 13, wherein the dose calculation points correspond with respective monitor units. 25. The computer product of claim 13, wherein the dose calculation points correspond with respective regions of a patient, respective collimator angles, respective couch positions, or respective couch angles. 26. A method for determining a radiation treatment plan, comprising: modeling a first part of a treatment plan using a fluence map; modeling a second part of the treatment plan using a first machine parameter, wherein the first part and the second part of the treatment plan correspond to different respective control points of the treatment plan, and the acts of modeling the first and second parts of the treatment plan are performed using a processor; and storing the treatment plan in a computer-readable medium. 27. The method of claim 26, wherein the fluence map comprises a matrix representing an amount of radiation passing through a spatial region. 28. The method of claim 26, wherein the first machine parameter is selected from the group consisting of leaf sequence, collimator position, gantry rotation speed, gantry position, couch position, beam activation signal, beam deactivation signal, dose, dose rate, beam energy, and beam type. 29. The method of claim 26, further comprising converting at least a part of the fluence map into a second machine parameter. 30. The method of claim 26, further comprising determining a dose using the fluence map. 31. A computer product having a set of instructions stored in a computer-readable medium, an execution of which causes a process to be performed, the process comprising: modeling a first part of a treatment plan using a fluence map; and modeling a second part of the treatment plan using a first machine parameter; wherein the first part and the second part of the treatment plan correspond to different respective control points of the treatment plan. 32. The computer product of claim 31, wherein the fluence map comprises a matrix representing an amount of radiation passing through a spatial region. 33. The computer product of claim 31, wherein the first machine parameter is selected from the group consisting of leaf sequence, collimator position, gantry rotation speed, gantry position, couch position, beam activation signal, beam deactivation signal, dose, dose rate, beam energy, and beam type. 34. The computer product of claim 31, wherein the process further comprises converting at least a part of the fluence map into a second machine parameter. 35. The computer product of claim 31, wherein the process further comprises determining a dose using the fluence map. 36. The computer product of claim 13, wherein the computer product comprises a processor for performing the acts of modeling the first and second parts of the treatment plan. 37. A method for determining a radiation treatment plan, comprising: determining a plurality of dose calculation points; determining a level of complexity of fluence for one of the plurality of dose calculation points using a processor; converting a fluence map to one or more machine parameters for the one of the plurality of dose calculation points based at least in part on the determined level of complexity; using the one or more machine parameters to determine a treatment plan; and storing the treatment plan in a computer-readable medium. 38. The method of claim 37, wherein the fluence map is converted when the determined level of complexity is below a prescribed threshold. 39. The method of claim 37, wherein the act of converting the fluence map is performed using a leaf sequencing algorithm. 40. The method of claim 37, further comprising performing fluence optimization using the plurality of dose calculation points. 41. The method of claim 37, wherein the dose calculation points correspond with respective gantry ranges. 42. The method of claim 37, wherein the dose calculation points correspond with respective time periods. 43. The method of claim 37, wherein the dose calculation points correspond with respective monitor units. 44. The method of claim 37, wherein the dose calculation points correspond with respective regions of a patient, respective collimator angles, respective couch positions, or respective couch angles. 45. A computer product having a set of instructions stored in a computer-readable medium, an execution of which causes a process to be performed, the process comprising: determining a plurality of dose calculation points; determining a level of complexity of fluence for one of the plurality of dose calculation points; and converting a fluence map to one or more machine parameters for the one of the plurality of dose calculation points based at least in part on the determined level of complexity. 46. The computer product of claim 45, wherein the fluence map is converted when the determined level of complexity is below a prescribed threshold. 47. The computer product of claim 45, wherein the act of converting the fluence map is performed using a leaf sequencing algorithm. 48. The computer product of claim 45, wherein the process further comprises performing fluence optimization using the plurality of dose calculation points. 49. The computer product of claim 45, wherein the dose calculation points correspond with respective gantry ranges. 50. The computer product of claim 45, wherein the dose calculation points correspond with respective time periods. 51. The computer product of claim 45, wherein the dose calculation points correspond with respective monitor units. 52. The computer product of claim 45, wherein the dose calculation points correspond with respective regions of a patient, respective collimator angles, respective couch positions, or respective couch angles. 53. The computer product of claim 45, wherein the computer product comprises a processor for performing the acts of determining, and the act of converting. 54. The method of claim 37, further comprising determining control points, wherein a first total number of the dose calculation points is fewer than a second total number of the control points. 55. The computer product of claim 45, wherein the process further comprises determining control points, wherein a first total number of the dose calculation points is fewer than a second total number of the control points.
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