Abstract #0617

Improving Respiratory Phase-resolved 3D Body Imaging Using Iterative Motion Correction and Average (MoCoAve)

Xiaoming Bi¹, Jianing Pang², Wensha Yang², Matthias Fenchel³, Zixin Deng², Yuhua Chen⁴, Richard Tuli², Debiao Li², Gerhard Laub¹, and Zhaoyang Fan²

¹Siemens Healthcare, Los Angeles, CA, United States, ²Cedars-Sinai Medical Center, Los Angeles, CA, United States, ³Siemens Healthcare GmbH, Erlangen, Germany, ⁴University of Pennsylvania, Philadelphia, PA, United States

4D (respiratory phase-resolved 3D) MRI has been increasingly used for the planning of radiotherapy and minimally invasive surgery. Recently developed self-gating methods showed great potential in 4D MRI by providing high imaging efficiency and isotropic spatial resolution. However, images of individual phases may suffer from decreased SNR and increased streaking artifact since only a subset of data were used for reconstruction. A motion correction and average (MoCoAve) framework was developed in this work to address such limitations. Preliminary results from patients showed that the proposed method can significantly improve SNR and image quality without compromising motion information.

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