2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDCIS-1.7
Paper Title A REGULARIZED APPROACH FOR RESPIRATORY MOTION ESTIMATION FROM SHORT-TIME PROJECTION DATA FRAMES IN EMISSION TOMOGRAPHY
Authors Andoni I. Garmendia, Yongyi Yang, Chao Song, Miles N. Wernick, Illinois Institute of Technology, Spain; P. Hendrik Pretorius, Michael A. King, University of Massachusetts Medical School, United States
SessionCIS-1: Computational Imaging Systems
LocationArea J
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Computational Imaging Systems: Tomographic Imaging
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Abstract Cardiac SPECT perfusion imaging is important for diagnosis and evaluation of coronary artery diseases. However, the acquired image data can suffer from motion blur due to patient respiratory motion. We propose a maximum-likelihood estimation (MLE) approach to determine a surrogate respiratory signal from short-time acquisition frames for motion correction. To compensate for the low data counts in the short-time frames, we employ a regularization term to exploit the similarity in acquired data among neighboring acquisition angles. In the experiments we validated this approach first on a set of simulated phantom data with known respiratory motion, and then on clinical acquisitions from 17 subjects. The results demonstrate that the proposed MLE approach could yield a reliable respiratory motion signal even with the acquisition frame duration being as short as 100ms, and outperformed both center-of-mass and Laplacian eigenmaps methods.