WAVELET-ACCELERATED REGULARIZATION METHODS FOR HYPERTHERMIA TREATMENTPLANNING

Cancer therapy by hyperthermia treatment aims to heat up the region of the tumor while keeping the surrounding body below a prespecified tem perature. The heating is achieved by an electromagnetic field generate d by several antennae which are placed around the patient. The hyperth ermia problem is to determine the parameters of the antennae, s.t. the resulting electromagnetic field is optimal with respect to some presc ribed quality criterion. Iterative optimization algorithms require the solution of large, dense linear systems in each iteration step. We in vestigated modifications of standard regularization methods for invers e problems where the system matrix A is replaced by a family of sparse approximations {A(k)}. An adaptation strategy for choosing the approx imation level, which leads to the same convergence rates as iteration schemes with the full matrix A, is proved. Wavelet compression techniq ues originally designed for applications in image processing are used to compute the approximating family {A(k)} leading to accelerated iter ation schemes. They are finally applied to optimize hyperthermia treat ment planning. (C) 1996 John Wiley & Sons, Inc.