Abstract #0788

Quantification and Artifact Reduction from Simple Modeling of DESS Signals

Bragi Sveinsson¹, Garry Gold¹, and Brian Hargreaves¹

¹Stanford University, Stanford, CA, United States

The double-echo in steady-state (DESS) sequence offers both 3D anatomical imaging and 3D quantitative mapping (SNR-efficient 3D maps of T2 and apparent diffusion coefficent) in various applications, such as breast imaging or knee cartilage imaging. The complicated signal behavior remains a challenge for quantitative imaging, and strong spoiling can lead to motion artifacts. Here, we introduce simplified methods for modeling DESS signals, enabling more accurate T2 measurements and better motion artifact reduction.

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