TY - JOUR
T1 - Treatment planning optimization by quasi-Newton and simulated annealing methods for gamma unit treatment system
AU - Shu, H. Z.
AU - Yan, Y. L.
AU - Bao, X. D.
AU - Fu, Y.
AU - Luo, L. M.
PY - 1998/10/1
Y1 - 1998/10/1
N2 - The gamma unit is used to irradiate a target within the brain. During such a treatment many parameters, including the number of shots, the coordinates, the collimator size and the weight associated with each shot, affect the amount of dose delivered to the target volume and to the surrounding normal tissues. Hence it is not easy to determine an appropriate set of these parameters by a trial and error method. For this reason, we present here an optimization method to determine mathematically those parameters. This method is composed of two steps: firstly, a quasi-Newton method is used to deal with the continuous variables such as position and weight of shots; the result obtained at the end of this step then serves as the initial configuration for the next step, in which a simulated annealing method is applied to optimize all the aforementioned parameters. Application of the proposed methods to two examples shows that our optimization algorithm runs in a satisfactory way.
AB - The gamma unit is used to irradiate a target within the brain. During such a treatment many parameters, including the number of shots, the coordinates, the collimator size and the weight associated with each shot, affect the amount of dose delivered to the target volume and to the surrounding normal tissues. Hence it is not easy to determine an appropriate set of these parameters by a trial and error method. For this reason, we present here an optimization method to determine mathematically those parameters. This method is composed of two steps: firstly, a quasi-Newton method is used to deal with the continuous variables such as position and weight of shots; the result obtained at the end of this step then serves as the initial configuration for the next step, in which a simulated annealing method is applied to optimize all the aforementioned parameters. Application of the proposed methods to two examples shows that our optimization algorithm runs in a satisfactory way.
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U2 - 10.1088/0031-9155/43/10/009
DO - 10.1088/0031-9155/43/10/009
M3 - Article
C2 - 9814518
AN - SCOPUS:0031688906
SN - 0031-9155
VL - 43
SP - 2795
EP - 2805
JO - Physics in Medicine and Biology
JF - Physics in Medicine and Biology
IS - 10
ER -