Abstract #2611

Automated streaking artifact suppression for multi-echo radial abdominal data compatible with advanced reconstruction techniques

Brian Toner¹, Shu-Fu Shih^2,3, Fei Han⁴, Eze Ahanonu⁵, Ute Goerke⁶, Kevin Johnson^7,8, Holden Wu^2,3, Maria Altbach^7,8,9, and Ali Bilgin^1,5,8,9

¹Program in Applied Mathematics, The University of Arizona, Tucson, AZ, United States, ²Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, ³Bioengineering, University of California Los Angeles, Los Angeles, CA, United States, ⁴Siemens Healthineers, Los Angeles, CA, United States, ⁵Electrical and Computer Engineering, The University of Arizona, Tucson, AZ, United States, ⁶Siemens Healthineers, Tucson, AZ, United States, ⁷Radiology, The University of Arizona, Tucson, AZ, United States, ⁸Medical Imaging, The University of Arizona, Tucson, AZ, United States, ⁹Biomedical Engineering, The University of Arizona, Tucson, AZ, United States

Synopsis

Keywords: Artifacts, Artifacts

Motivation: Streaking artifacts, often emanating from the arms, are a major issue in radial abdominal imaging. Solutions typically consist of estimating coil sensitivity maps that suppress artifacts and often ignore phase information

Goal(s): To suppress streaking artifacts with a method that will not disrupt phase in multi-echo data and be easily incorporated into existing reconstruction algorithms.

Approach: Modifying an existing coil-domain method that can be applied directly to k-space or coil sensitivity maps for reconstruction of multi-echo data.

Results: The proposed method out-performed existing artifact suppression techniques and improved the reconstruction of water and fat images coming from multi-echo data.

Impact: The proposed destreaking method was demonstrated to be equivalent when applied to multi-coil images, multi-coil k-space, or coil sensitivity maps, providing flexibility when being incorporated into existing reconstruction algorithms. It out-performed existing techniques and improved the reconstruction of multi-echo data.

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