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Myocardium extraction in positron emission tomography based on soft computing

✍ Scribed by F. Behloul; A. Boudraa; B.P.F. Lelieveldt; M. Janier; J.H.C Reiber


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
844 KB
Volume
25
Category
Article
ISSN
0895-6111

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✦ Synopsis


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.


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