D.RE.A.M.: A software for uncertainties analysis in retrospective dosimetry

Abstract

Accidental exposures to ionising radiations are nowadays managed with assistance from biological and physical retrospective dosimetry which are able to provide individual estimates of dose absorbed by victims. The aim of this work is to describe the development of biodosimetry analysis software within the "EURADOS Working Group 10—Retrospective dosimetry" Task group 10.6. Methods The software has been developed in Python code language that is easy to learn, read, use and extensible (it is possible to add new modules). It can implement C/C++/Fortran, Java functions. It is embeddable in applications and is open source. It is extremely portable to Unix/Linux, Windows, Mac operating systems. The memory management is automatic. The software uses many free scientific python packages (such as numpy, scipy and sympy) and has a user-friendly graphical user interface. Results The software developed was named "Dose REconstruction by Analytical and Monte carlo methods" (D.RE.A.M.) and enables performance of uncertainties analyses though various mathematical methods. In particular, it facilitates: Analytical calculation of combined standard uncertainties Monte Carlo estimation of combined uncertainties Dose reconstruction from least square calibration curves by 1) analytical inversion of the calibration curve function 2) Monte Carlo calculation Dose reconstruction with using Bayesian Method (Markov Chain Monte Carlo Method). This last analysis is still under validation process. After complete validation process this software will be freely available for everybody and will guide the user to the requested results.