INTRODUCTION OF A MULTIAGENT PARADIGM TO OPTIMIZE A CASE-BASED REASONING SYSTEM DESIGNED TO PERSONALIZE THREE-DIMENSIONAL NUMERICAL REPRESENTATIONS OF HUMAN ORGANS

Abstract

The case-based reasoning (CBR) approach consists of retrieving solutions from similar past problems and adapting them to new problems. Interpolation tools can easily be used as adaptation tools in CBR systems. The accuracies of interpolated results depend on the set of known solved problems with which the interpolation tools are previously trained. EquiVox is a CBR-based system designed for retrieving and adapting three-dimensional numerical representations of human organs called phantoms. EquiVox uses an interpolation tool as an adaptation process. These phantoms are used by radiation protection experts to establish dosimetric reports in case of accidental overexposure to radiation. In addition, medical physicians need these phantoms to compute and control exposure to radiation used to treat diseases such as cancerous tumors in hospitals. The present work aims at proposing a distributed architecture for EquiVox so that a user may find a solution as quickly as possible based on the most recent available knowledge of a given community. We have designed a distributed architecture based on a multiagent paradigm and studied the theoretical performance of the new version. The ability of the new system to quickly provide and adapt solutions using the most up-to-date knowledge has been analyzed from a probabilistic angle. In the case of limited and accidental exposure to radiation, the proposed parallel processing system improves the previous and sequential version of EquiVox. Improvements are also obtained in some cases of massive exposure to radiation.