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Abstract #3994

A Machine Learning Based Approach for Fast T1 estimation with Improved Accuracy

Anirban Sengupta1, Rakesh Kumar Gupta2, Sumeet Agarwal3, and Anup Singh4

1CBME, IIT Delhi, New Delhi, India, 2Radiology Department, FORTIS hospital,Gurgaon, India, 3Electrical Engineering, IIT Delhi, India, 4Centre for Biomedical Engineering, IIT Delhi; AIIMS Delhi, New Delhi, India

The purpose of this study is to propose a fast T1 estimation method with improved accuracy over existing approaches in a Multiple Flip Angle setting. A supervised machine learning based approach has been proposed that can be used to predict additional Flip Angle data using limited available Flip Angle data, thereby producing more accurate T1 estimation in reduced scan time. Both experimental as well as simulation results are shown to illustrate the efficacy of this approach. The accuracy of T1 estimation depends on the choice of Flip Angle data to be predicted.

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