Myocardium extraction in positron emission tomography based on soft computing

This paper presents an efficient and accurate approach to myocardium extrac tion in Positron Emission Tomography (PET) images based on a careful applic ation of soft computing techniques. PET images present a noisy background, making the automatic myocardium extraction and uptake quantification a diff icult task. In this work a Self Organized Radial Basis Function Network (SR BFN) is designed to focus on the myocardium in an iterative process until t he total extraction of the myocardium from the noisy background is achieved . Fuzzy sets and fuzziness measures are used to compute the error of the ne twork. The method was tested on a set of nine images of different patients and its effectiveness is illustrated in two patients showing tracer uptake defects. (C) 2001 Elsevier Science Ltd. All rights reserved.