Author/Authors :
Nouri S. نويسنده Department of Physics, Faculty of Basic Sciences, Islamic Azad University, Central Tehran Branch, Iran , Hosseini Pooya S. M. نويسنده Radiation Application Research School, Nuclear Science & Technology Research Institute, AEOI, Tehran, Iran , Soltani Nabipour J. نويسنده Department of Physics, Islamic Azad University, Parand Branch, Iran
Abstract :
Background: The motions of body and tumor in some regions such as chest
during radiotherapy treatments are one of the major concerns protecting normal
tissues against high doses. By using real-time radiotherapy technique, it is possible
to increase the accuracy of delivered dose to the tumor region by means of tracing
markers on the body of patients.
Objective: This study evaluates the accuracy of some artificial intelligence
methods including neural network and those of combination with genetic algorithm
as well as particle swarm optimization (PSO) estimating tumor positions in real-time
radiotherapy.
Method: One hundred recorded signals of three external markers were used as input
data. The signals from 3 markers thorough 10 breathing cycles of a patient treated
via a cyber-knife for a lung tumor were used as data input. Then, neural network
method and its combination with genetic or PSO algorithms were applied determining
the tumor locations using MATLAB© software program.
Results: The accuracies were obtained 0.8%, 12% and 14% in neural network,
genetic and particle swarm optimization algorithms, respectively.
Conclusion: The internal target volume (ITV) should be determined based on the
applied neural network algorithm on training steps.
