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Abstract #3716

A frequency-domain machine learning (FML) method for dual-calibrated estimation of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen metabolism (CMRO2)

Michael Germuska1, Hannah L Chandler1, Rachael C Stickland1, Catherine Foster2, Jessica Steventon1, Valentina Tomassini1, Kevin Murphy1, and Richard G Wise1

1Cardiff University, Cardiff, United Kingdom, 2Concordia University, Montreal, QC, Canada

A frequency-domain machine learning method is presented that significantly reduces the bias and variance in dual-calibrated estimation of oxygen extraction fraction, as demonstrated with simulation and in-vivo imaging. In addition, the method substantially reduces the processing time compared to previous robust analysis methods.

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