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Abstract #2508

Improved Myelin Content Estimates from Clinical Selective Inversion Recovery Scans via Anisotropic Filtering

Mohammadreza Soltany Sadrabadi1, Ashley M. Stokes1, and Richard Dortch1
1Barrow Neurological Institute, Phoenix, AZ, United States

Synopsis

Keywords: Multiple Sclerosis, Multiple Sclerosis

Motivation: Traditionally, Selective Inversion Recovery (SIR) images require long scan times for sufficient SNR, while shorter clinical scans yield low SNR images with noisy pool-size-Ratio (PSR) maps, leading to potential inaccuracies.

Goal(s): An advanced filtering method has been used to improve the precision and accuracy of PSR maps from lower SNR scans.

Approach: An advanced filtering method has been used to improve the precision and accuracy of PSR maps from lower SNR scans.

Results: Initial results demonstrate that this method produces PSR maps comparable to longer, higher SNR scans from shorter clinical scans.

Impact: The implementation of nonlinear anisotropic filtering methods significantly improves the practicality of SIR imaging in a clinical setting, offering quick, accurate myelin content assessments (without blurring tissue boundaries like linear filters) for applications in MS.

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