Improvements in Radiation Therapy Plan Optimization
(Mark Phillips, Juergen Meyer, Ira Kalet)
Treatment planning optimization has recently received much attention due to the advent of inverse planning techniques for IMRT. As useful as these algorithms are, they all have difficulty in handling the predominant situations in radiation therapy. These problems include decisions based on models formulated with incomplete data, incomplete and qualitative presriptions, and mutually contradictory constraints/objectives. Our project is aimed at using belief nets (also known as Bayes' nets) to provide better methods at guiding the optimization process and choosing the most clinically appropriate solution.