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Parametric Imaging with Respiratory Motion Correction for Contrast-Enhanced Ultrasonography

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초록

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast- enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

Abstract

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast- enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

참고문헌 (18)

  1. 3 Feb, "2015", ~
  2. X. Ma, "Application of Contrast-Enhanced Ultrasound(CUES) in lymphomatous lymph nodes: a comparison between PET", CT and Contrast-Enhanced CT, 2019, pp.2019, ~
  3. N. Li, "Intrahepatic transit time predicts liver fibrosis in patients with chronic hepatitis B : quantitative assessment with contrast-enhanced ultrasonography", Ultrasound in Medicine and Biology, 36(7), pp.1066~1075 (2010)
  4. N. Rognin, "Parametric imaging for characterizing focal liver lesions in contrast-enhanced ultrasound", IEEE Transaction on Ultrasonics, Ferroelectrics, and Frequency Control, 57(11), pp.2503~2511 (2010)
  5. R. Iezzi, "The role of contrast-enhanced ultrasound(CEUS)in visualizing atherosclerotic carotid plaque vulnerability : Which injection protocol? Which scanning technique", European Journal of Radiology, 84(1), pp.865~871 (2015)
  6. L. Chiorean, "Focal masses in a non-cirrhotic liver : The additional benefit of CEUS over baseline imaging", European Journal of Radiology, 84(1), pp.1636~1643 (2015)
  7. A. Lim, "Hepatic vein transit times using a microbubble agent can predict disease severity noninvasively in patients with hepatitis C", Gut, 54(1), pp.128~133 (2005)
  8. S. Wilson, "An algorithm for the diagnosis of focal liver masses using microbubble contrast-enhanced pulse-inversion sonography", American Journal of Roentgenology, 186(1), pp.1401~1411 (2006)
  9. C. Dietrich, "Characterisation of focal liver lesions with contrast enhanced ultrasonography", European Journal of Radiology, 10(11), pp.9~17 (2003)
  10. J. McClelland, "Respiratory motion models : a review", Medical Image Analysis, 17(1), pp.19~42 (2013)
  11. J. Zhang, "Respiratory motion correction in free-breathing ultrasound image sequence for quantification of hepatic perfusion", Medical Physics, 38(1), pp.4737~4748 (2011)
  12. M. Nakamoto, "Recovery of respiratory motion and deformation of the liver using laparoscopic freehand 3d ultrasound system", Medical Image Analysis, 11(5), pp.429~442 (2007)
  13. S. Mule, "An automatic respiratory gating method for the improvement of microcirculation evaluation : application to contrast-enhanced ultrasound studies of focal liver lesions", Physics in Medicine and Biology, 56(1), pp.5153~5165 (2011)
  14. V. Hamy, "Respiratory motion correction in dynamic MRI using robust data decomposition registration-Application to DCE-MRI", Medical Image Analysis, 18(2), pp.301~313 (2014)
  15. W. Jiang, "Respiratory motion correction in abdomical MRI using a densely connected U-Net with GAN-guided training", arxiv : 2906. 09745, ~ (2019)
  16. J. Gance, "Target detection and tracking of moving objects for characterizing landslide displacement from time-lapse terrestrial optical image", Engineering Geology, 172(1), pp.26~40 (2014)
  17. X. Qian, "An object tracking method based on local matting for night fusion image", Infrared Physics & Technology, 67(1), pp.455~461 (2014)
  18. J. Yan, "Robust object tracking using least absolute deviation", Image and Vision Computing, 32(1), pp.930~939 (2014)

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