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Abstract #4017

Deep-learning-based phase correction during reconstruction of high-resolution, multi-shot reduced-FOV pancreatic DWI.

Ryan L Brunsing1, Alexandra H Besser2, Arnaud Guidon3, Xinzeng Wang3, and Patricia Lan3
1Radiology, Stanford, Stanford, CA, United States, 2Stanford, Stanford, CA, United States, 3GE Healthcare, Waukesha, WI, United States

Synopsis

Keywords: Pancreas, Diffusion/other diffusion imaging techniques, Pancreas, Deep-learning, Phase Correction, DWI, rFOV, multishot, SNR

Motivation: Diffusion weighted imaging (DWI) is valuable in pancreatic imaging but suffers from artifacts and low SNR. The combination of reduced FOV imaging with a multishot data sampling strategy (rFOV-msDWI) improves artifacts from susceptibility and allows higher achievable resolution but still suffers from low SNR.

Goal(s): Here we report early findings from an ongoing pilot study

Approach: Evaluate a DL-based phase correction algorithm for improved SNR in patients undergoing rFOV-msDWI of the pancreas.

Results: DL-based phase correction subjectively improves image quality.

Impact: DL-based phase correction may improve rFOV-msDWI of the pancreas. Further evaluation is warranted.

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Keywords