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Abstract #2495

SNR Quantification using Pseudoreplica Method: Validation in Phantom and Application to in-vivo Brain Perfusion using ASL

Sebastian Fonseca1, Keith Hulsey1, Limin Zhou1, Ivan Dimitrov2, Johannes M Peeters3, and Ananth Madhuranthakam1,4
1Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2Philips Healthcare, Dallas, TX, United States, 3Philips Healthcare, Best, Netherlands, 4Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Synopsis

Keywords: Data Processing, Quantitative Imaging, SNR, ASL, Brain

Motivation: SNR is a key image quality metric; however estimating it can be difficult when using more complex image acquisition and reconstruction techniques.

Goal(s): Demonstrate the validity of the pseudoreplica method as an accurate SNR estimation tool and show potential for its translation into clinical scanning protocols.

Approach: We quantified SNR using our pseudoreplica method implementation in MATLAB in a prostate phantom, as well as in a brain ASL dataset of healthy volunteers.

Results: SNR values obtained with the pseudoreplica method in the prostate phantom and in-vivo brain ASL dataset had good agreement with the multiple and dual acquisition SNR quantification methods.

Impact: We have demonstrated the reliability and accuracy of our pseudoreplica SNR quantification implementation in ASL. Integrating this method into the scanner's pipeline would allow for real-time assessment of image quality and further optimization of new MR sequences and reconstruction methods.

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Keywords