Bulk motion detection and correction using list-mode data for cardiac PET imaging

Tao Sun; Yoann Petibon; Paul Han; Chao Ma; Sally J. W. Kim; Nathaniel M. Alpert; Georges El Fakhri; Jinsong Ouyang

doi:10.1117/12.2534701

Translator Disclaimer

28 May 2019 Bulk motion detection and correction using list-mode data for cardiac PET imaging

Tao Sun, Yoann Petibon, Paul Han, Chao Ma, Sally J. W. Kim, Nathaniel M. Alpert, Georges El Fakhri, Jinsong Ouyang

Author Affiliations +

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 110722F (2019) https://doi.org/10.1117/12.2534701
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

Purpose: Image quality of cardiac PET is degraded by cardiac, respiratory, and bulk motion. The purpose of this work is to use PET list-mode data to detect and correct for bulk motion, which is unpredictable and must therefore be tracked at all times. Methods: We propose a data-driven approach that can detect and compensate bulk motion in cardiac PET imaging. Events in a motion-contaminated scan are binned into static (without intra-frame motion) and moving (with intra-frame motion) frames based on the variance of the center positions of line-of-responses calculated in each 1-second time window. Each moving frame is further divided into subframes, within which no motion is assumed. Data in each static and sub-moving-frame are then back-projected to the image space. The resulting images are used to estimate motion transformation from all static and sub-moving frames to a selected static reference frame. Finally, the data in all the frames are jointly reconstructed by incorporating motion estimation in the system matrix. We have applied our method to three human cardiac PET studies. Results: Visual assessment indicated the greatly improved image quality of the motion-corrected image over non-motion-corrected image. Also, motion correction yielded higher myocardium to blood pool concentration ratios than non-motion correction. Conclusion: The proposed bulk motion correction method improves the image quality of cardiac PET and can potentially be applied to other PET imaging applications such as brain PET.

Citation Download Citation

Tao Sun, Yoann Petibon, Paul Han, Chao Ma, Sally J. W. Kim, Nathaniel M. Alpert, Georges El Fakhri, and Jinsong Ouyang "Bulk motion detection and correction using list-mode data for cardiac PET imaging", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110722F (28 May 2019); https://doi.org/10.1117/12.2534701

ACCESS THE FULL ARTICLE