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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