FMRI unmixing via properly adjusted dictionary learning. Kopsinis, Y., Georgiou, H., & Theodoridis, S. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 2075-2079, Sep., 2014.
Paper abstract bibtex The mapping of the functional networks within the brain is a major step towards a deeper understanding of the the brain function. It involves the blind source separation of obtained fMRI data, usually performed via independent component analysis (ICA). Recently, there is an increased interest for alternatives to ICA for data-driven fMRI unmixing and notably good results have been attained with Dictionary Learning (DL) - based analysis. In this paper, the K-SVD DL method is appropriately adjusted in order to cope with the special properties characterizing the fMRI data.
@InProceedings{6952755,
author = {Y. Kopsinis and H. Georgiou and S. Theodoridis},
booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
title = {FMRI unmixing via properly adjusted dictionary learning},
year = {2014},
pages = {2075-2079},
abstract = {The mapping of the functional networks within the brain is a major step towards a deeper understanding of the the brain function. It involves the blind source separation of obtained fMRI data, usually performed via independent component analysis (ICA). Recently, there is an increased interest for alternatives to ICA for data-driven fMRI unmixing and notably good results have been attained with Dictionary Learning (DL) - based analysis. In this paper, the K-SVD DL method is appropriately adjusted in order to cope with the special properties characterizing the fMRI data.},
keywords = {biomedical MRI;blind source separation;brain;independent component analysis;learning (artificial intelligence);medical image processing;neurophysiology;singular value decomposition;functional networks;brain function;blind source separation;independent component analysis;ICA;data-driven fMRI unmixing;dictionary learning based analysis;DL based analysis;K-SVD DL method;Dictionaries;Vectors;Sparse matrices;Correlation;Encoding;Matching pursuit algorithms;Brain;Matrix Factorization;fMRI;Blind Source Separation;Dictionary Learning},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569926909.pdf},
}
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