Study of data analysis methods in functional connectivity photoacoustic tomography (fcPAT)

Afsoon Khodaee; Mohammadreza Nasiriavanaki

doi:10.1117/12.2254341

23 March 2017 Study of data analysis methods in functional connectivity photoacoustic tomography (fcPAT)

Afsoon Khodaee, Mohammadreza Nasiriavanaki

Proceedings Volume 10064, Photons Plus Ultrasound: Imaging and Sensing 2017; 1006438 (2017) https://doi.org/10.1117/12.2254341
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Resting-state functional connectivity (RSFC) is a method to monitor the health of the brain and find out abnormalities in brain networks. Recently functional connectivity photoacoustic tomography (fcPAT) has been used to study RSFC in the mouse brain. The current method of RSFC data analysis is called “seed-based”. This method is not data-driven, and involves user intervention. Alternative signal processing approaches, such as singular value decomposition (SVD) and independent component analysis (ICA), will be explored to complement and cross validate the seed-based approach, possibly substituting them for the seed-based method. The methods are implemented and applied on the fcPAT data of a mouse brain.

Citation Download Citation

Afsoon Khodaee and Mohammadreza Nasiriavanaki "Study of data analysis methods in functional connectivity photoacoustic tomography (fcPAT)", Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 1006438 (23 March 2017); https://doi.org/10.1117/12.2254341

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