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Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis
2013
International Journal of Image Graphics and Signal Processing
In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis.
doi:10.5815/ijigsp.2013.08.04
fatcat:c4f3rrlczjbhxmkt4xtps2xuj4