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Abstract #4332

Application of Partial Least Squares regression for Fast and Robust Dictionary Matching for Magnetic Resonance Fingerprinting

Shivaprasad Ashok Chikop1, Vimal Chandran2, Imam Shaik1, Rashmi Rao1, Mauricio Antonio Reyes Aguirre2, and Sairam Geethanath1

1Medical Imaging Research Center, Dayananda Sagar Institutions, Bangalore, India, 2Institute of Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland

The step size of the parameters used for simulation of dictionary determines the parameters being determined. Partial Least squares (PLS) can be used as a general frame work for fast and robust dictionary matching. Regression co-efficient matrix obtained from PLS can be used for localizing the different brain tissue types thus avoiding iterative searching. The increase in contrast between the grey matter and white matter can be attributed to the intermediate values generated by PLS based matching. PLS matches comparatively better at low SNR images compared to the straight forward dot product method.

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