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Journal of Medical and Biological Engineering

, Volume 38, Issue 2, pp 173–185 | Cite as

Combination of Window-Modulated Ultrasound Nakagami Imaging and Gaussian Approximation for Radiofrequency Ablation Monitoring: An In Vitro Study

  • Xin Guan
  • Heng Du
  • Qiang Li
  • Po-Hsiang Tsui
Original Article
First Online:
Received:
Accepted:
  • 65 Downloads

Abstract

The ultrasound Nakagami parameter map efficiently describes the statistical properties of the liver tissue. Using sliding windows in Nakagami imaging for monitoring radiofrequency ablation (RFA) is feasible. However, a limitation of conventional Nakagami imaging is the inability to visualize precise ablation (necrosis) zones by using a single sliding window. To accurately estimate ablation zones, we used window-modulated compounding (WMC) Nakagami imaging based on the synthesis of Nakagami images by using windows of different side lengths. Moreover, we proposed a new strategy for the postprocessing of Nakagami images by using Gaussian approximation (GAX) to approximate the cross-sectional areas of ablation zones. We heated 15 porcine liver samples for 12 min by using electrodes of tip lengths 0.5, 1.0, and 1.5 cm to ensure tissue necrosis after the ablation. The contour area of −6 dB in two-dimensional (2D) GAX images increased from 41 to 209 mm2, whereas that in the measures of section images increased from 40 to 265 mm2, with an increase in the electrode tips length from 0.5 to 1.5 cm. The coefficient of determination between the contour area of −6 dB in 2D GAX images and that in the measures of section images was 0.97, indicating a more satisfactory performance of GAX compared with that of polynomial approximation. The area estimated using GAX was similar to a circle, which conformed to the physical process of RFA.

Keywords

Ultrasound Compounding Nakagami imaging Radiofrequency ablation Gaussian approximation 
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Notes

Acknowledgement

The use of facilities was supported by Ultrasound Imaging Lab, Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan. This work was also supported by the National Natural Science Foundation of China (No. 61471263).

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Copyright information

© Taiwanese Society of Biomedical Engineering 2017

Authors and Affiliations

  1. 1.School of Electronic Information EngineeringTianjin UniversityTianjinPeople’s Republic of China
  2. 2.Department of Medical Imaging and Radiological Sciences, College of MedicineChang Gung UniversityTaoyuanTaiwan
  3. 3.Medical Imaging Research Center, Institute for Radiological ResearchChang Gung University and Chang Gung Memorial Hospital at LinkouTaoyuanTaiwan
  4. 4.Department of Medical Imaging and InterventionChang Gung Memorial Hospital at LinkouTaoyuanTaiwan

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