Name
Abstract | ||
|---|---|---|
In this paper, a synergy of signal processing techniques and intelligent strategies is applied in order to identify different types of human brain tumours, so that to help to confirm the histological diagnosis. The wavelet-SVM (support vector machine) classifier merges wavelet transform to reduce the size of the biomedical spectra and to extract the main features, with SVM to classify them. The influence of some of the configuration parameters of each of those techniques on the clustering is analysed. The classification results are promising specially taking into account that medical knowledge has not been considered. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ISKE.2008.4731161 | Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference |
Keywords | DocType | Volume |
cancer,medical signal processing,patient diagnosis,support vector machines,wavelet transforms,biomedical spectra,brain tumour diagnosis,histological diagnosis,human brain tumours,intelligent strategies,signal processing techniques,correlation,support vector machine,signal processing,wavelet transform,feature extraction | Conference | 1 |
ISBN | Citations | PageRank |
978-1-4244-2197-8 | 4 | 0.69 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farias, G. | 1 | 4 | 0.69 |
| M. Santos | 2 | 16 | 3.93 |
| Lopez, V. | 3 | 4 | 0.69 |