Optimization of Human Cancer Radiotherapy

algorithm anoxic cells application approach assumed attenuation coefficient benefit function cancer cell cycle cell population Chapter clinical Cohen computerized tomography conjugate gradient method considered constraints contour costate equation curves damage Define denote density determine dosage dose distribution dose fractions Dynamic Programming equation example field Figure fractionation scheme given gives gradient method Hence hypoxic cells integral irradiation isodose iteration kinetic linear programming linear programming problems mathematical model maximum minimization nonlinear nonlinear programming normal cells normal tissue number of cells number of fractions obtained optimal control problems oxygenated cells parameters patient penalty function performance criterion phase present probability procedure quadratic programming quantity radiation dose radiation therapy radiation treatment radiotherapy Radon transform rads ratio reconstruction score function Section selected solution survival expression surviving fraction target technique therapeutic tion tomography total dose treatment plan tumor cells tumor model values variables vector X-ray zero