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Abstract #5228

A Mixed Precision Conjugate Gradient Method for Efficient Iterative MRI reconstruction

Nikhil Deveshwar1,2 and Peder E. Z. Larson1,2
1Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, 2UC Berkeley - UCSF Graduate Program in Bioengineering, San Francisco, CA, United States

Synopsis

Keywords: Image Reconstruction, Image Reconstruction, mixed-precision arithmetic

Motivation: Iterative MRI reconstruction algorithms are computational expensive requiring expensive compute to implement.

Goal(s): Investigate the feasibility of mixed-precision arithmetic for an iterative MRI reconstruction algorithm.

Approach: Different mixed precision versions of conjugate gradient method were implemented with 32-bit floating point, 16-bit floating point, and 8-bit floating point representations and the quality of the reconstructed image was assessed.

Results: The mixed-precision floating point 8-bit algorithm shows numerical instability but decent performance with an increased in regularization compared to 32-bit and 16-bit floating point versions.

Impact: Iterative reconstruction algorithms could possibly be implemented on low performance and cheaper compute hardware with further algorithmic stability enhancements.

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Keywords