Myocardium extraction in positron emission tomography based on soft computing.
This paper presents an efficient and accurate approach to myocardium extraction in Positron Emission Tomography (PET) images based on a careful application of soft computing techniques. PET images present a noisy background, making the automatic myocardium extraction and uptake quantification a difficult task. In this work a Self Organized Radial Basis Function Network (SRBFN) is designed to focus on the myocardium in an iterative process until the total extraction of the myocardium from the noisy background is achieved. Fuzzy sets and fuzziness measures are used to compute the error of the network. 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.
Behloul
F
F
Division of Image Processing (LKEB), Department of Radiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC, Leiden, Netherlands.
Boudraa
A
A
Lelieveldt
B P
BP
Janier
M
M
Reiber
J H
JH
D019788:Fluorodeoxyglucose F18; D017143:Fuzzy Logic; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D014055:Tomography, Emission-Computed / Q000379:methods*
D019788:Fluorodeoxyglucose F18