적응 대역필터를 이용한 의료 초음파 감쇠 예측Estimation of Medical Ultrasound Attenuation using Adaptive Bandpass Filters
- Other Titles
- Estimation of Medical Ultrasound Attenuation using Adaptive Bandpass Filters
- Authors
- 허서원; 이준환; 김형석
- Issue Date
- 2010
- Publisher
- 대한전자공학회
- Keywords
- medical ultrasound; attenuation; VSA method; bandpass filter; quantitative ultrasound analysis
- Citation
- 전자공학회논문지 - SC, v.47, no.5, pp.43 - 51
- Journal Title
- 전자공학회논문지 - SC
- Volume
- 47
- Number
- 5
- Start Page
- 43
- End Page
- 51
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/21163
- ISSN
- 1229-6392
- Abstract
- Attenuation coefficients of medical ultrasound not only reflect the pathological information of tissues scanned but also provide the quantitative information to compensate the decay of backscattered signals for other medical ultrasound parameters. Based on the frequency-selective attenuation property of human tissues, attenuation estimation methods in spectral domain have difficulties for real-time implementation due to the complexicity while estimation methods in time domain do not achieve the compensation for the diffraction effect effectively. In this paper, we propose the modified VSA method, which compensates the diffraction with reference phantom in time domain, using adaptive bandpass filters with decreasing center frequencies along depths. The adaptive bandpass filtering technique minimizes the distortion of relative echogenicity of wideband transmit pulses and maximizes the signal-to-noise ratio due to the random scattering, especially at deeper depths. Since the filtering center frequencies change according to the accumulated attenuation, the proposed algorithm improves estimation accuracy and precision comparing to the fixed filtering method. Computer simulation and experimental results using tissue-mimicking phantoms demonstrate that the distortion of relative echogenicity is decreased at deeper depths, and the accuracy of attenuation estimation is improved by 5.1% and the standard deviation is decreased by 46.9% for the entire scan depth.
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Collections - College of Engineering > School of Electronic & Electrical Engineering > 1. Journal Articles
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