Biological Dose Optimization Using the Levenberg-Marquardt Method
نویسندگان
چکیده
The treatment planning software TRiP98 [1, 2, 3] is successfully used in the ion therapy project at GSI. A crucial part of the treatment planning is the particle number optimization in order to achieve a target dose distribution as close as possible to the prescribed biological dose distribution. The optimization task can be expressed mathematically by the minimization of a multidimensional objective function by means of the least squares method. In this contribution we examine the Levenberg-Marquardt method (LMM), used to handle the optimization problem.
منابع مشابه
Large Deformation Characterization of Mouse Oocyte Cell Under Needle Injection Experiment
In order to better understand the mechanical properties of biological cells, characterization and investigation of their material behavior is necessary. In this paper hyperelastic Neo-Hookean material is used to characterize the mechanical properties of mouse oocyte cell. It has been assumed that the cell behaves as continuous, isotropic, nonlinear and homogenous material for modeling. Then, by...
متن کاملMaterial Decomposition for Energy Resolving Detectors using Weighted Levenberg-Marquardt Optimization
Introduction: Energy resolving X-ray photon counting detectors are able to assign each detected photon to energy bins [1] (Figure 1). This allows the decomposition of an X-ray image into the materials of the acquired object [1, 2], which has potential benefits in angiography. Contrast agent can be extracted without acquiring a mask image, possibly saving dose and avoiding problems with patient ...
متن کاملLevenberg Marquardt ( LM ) Algorithm 1 –
1 – Introduction Parameter estimation for function optimization is a well established problem in computing, as there are countless applications in practice. For this work, we will focus specifically in implementing a distributed and parallel implementation of the Levenberg Marquardt algorithm, which is a well established numerical solver for function approximation given a limited data set. Para...
متن کاملThe based on optimization LM learning techniques is used for nonlinear oscillatory plant identification and oscillation suppression by means of a direct integral term (I-term) adaptive neural control using RCVNN. Lastly,
In this work, a recursive Levenberg-Marquardt (LM) learning algorithm in the complex domain is developed and applied to the learning of an adaptive control scheme composed by ComplexValued Recurrent Neural Networks (CVRNN). We simplified the derivation of the LM learning algorithm using a diagrammatic method to derive the adjoint CVRNN used to obtain the gradient terms. Furthermore, we apply th...
متن کاملCSLMEN: A New Optimized Method for Training Levenberg Marquardt Elman Network Based Cuckoo Search Algorithm
RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...
متن کامل