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논문검색

A Centralized Displacement Operation with Application to Artifact Reduction in Ultrasonic Elastography

초록

영어

Because stiff tissue deforms less than soft tissue under the same external compression, elastography can provide relative stiffness information of biological tissue. However, elastography suffers from artifact noise which may come from two dominant sources: de-correlation error and amplitude modulation error. In order to reduce artifacts and improve the quality of ultrasonic elastography, this paper proposes a centralized displacement operation based on an adaptive anisotropic diffusion filtering. We have applied the median and the mean of displacement axial gradient to differentiate edges from artifacts and categorize the whole displacement image into two different patterns; followed by the adjustable anisotropic diffusion filtering. The proposed algorithm can reduce artifact noise and, at the same time, maintain the tissue structure. Phantom testing shows that the proposed method can improve the quality of ultrasonic elastography in terms of tissue SNRe and CNRe values.

목차

Abstract
 1. Introduction
 2. Method
  2.1. Centralized Displacement
  2.2 Centralized Displacement Operation
  2.3. The Algorithm
 3. Results and Discussion
  3.1. Criteria for Quantifying Algorithm Performance
  3.2. Phantom Image
  3.3. Discussion
 4. Conclusion
 Acknowledgements
 References

저자정보

  • Dangguo Shao Faculty of Information Engineering and Automation, KunMing University of Science and Technology, KunMing, China
  • Yong Chen Faculty of Information Engineering and Automation, KunMing University of Science and Technology, KunMing, China
  • Sanli Yi Faculty of Information Engineering and Automation, KunMing University of Science and Technology, KunMing, China
  • Lei Ma Faculty of Information Engineering and Automation, KunMing University of Science and Technology, KunMing, China
  • Jianfeng He Faculty of Information Engineering and Automation, KunMing University of Science and Technology, KunMing, China
  • Dong C. Liu School of Computer Science, Sichuan University, Chengdu, China

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