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Abstract #3157

A novel T2 relaxation analysis method SAME-ECOS: Spectrum Analysis for Multiple Exponentials via Experimental Condition Oriented Simulation

Hanwen Liu1,2, Qing-San Xiang1,3, Roger Tam3,4, Piotr Kozlowski3, David K.B. Li3, Alex L. MacKay1,3, John K. Kramer2,5, and Cornelia Laule1,2,3,6
1Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada, 2International Collaboration on Repair Discoveries, Vancouver, BC, Canada, 3Radiology, University of British Columbia, Vancouver, BC, Canada, 4Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada, 5Kinesiology, University of British Columbia, Vancouver, BC, Canada, 6Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada

We propose a novel T2 relaxation data analysis method called spectrum analysis for multiple exponentials via experimental condition oriented simulation (SAME-ECOS), which was developed based on a combination of information theory and deep learning neural network algorithms. SAME-ECOS is tailored for different MR experimental conditions to decompose the multi-exponential decay data into a T2 spectrum, which has been considered an ill-posed problem using conventional fitting algorithms including the commonly used non-negative least squares (NNLS). Our results demonstrated that, compared with NNLS, SAME-ECOS can yield much more reliable T2 spectra in a dramatically shorter time.

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