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Soft Computing
Published in: Soft Computing 12/2010

01-10-2010 | Focus

Making decisions on brain tumor diagnosis by soft computing techniques

Authors: G. Farias, M. Santos, V. López

Published in: Soft Computing | Issue 12/2010

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Abstract

In this paper, a synergy of advanced signal processing and soft computing strategies is applied in order to identify different types of human brain tumors, as a help to confirm the histological diagnosis of experts and consequently to facilitate the decision about the correct treatment or the necessity of an operation. A computational tool has been developed that merges, on the one hand, wavelet transform to reduce the size of the biomedical spectra and to extract the main features, and on the other hand, Support Vector Machine and Neural Networks to classify them. The influence of some of the configuration parameters of each of those soft computing techniques on the clustering is analyzed. These two methods and another one based on medical knowledge are compared. The classification results obtained by these computational tools are promising specially taking into account that medical knowledge has not been considered and that the number of samples of each class is very low in some cases.
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Metadata
Title
Making decisions on brain tumor diagnosis by soft computing techniques
Authors
G. Farias
M. Santos
V. López
Publication date
01-10-2010
Publisher
Springer-Verlag
Published in
Soft Computing / Issue 12/2010
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-009-0495-0

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