Minimum variance image blending for robust ultrasound image deconvolution

التفاصيل البيبلوغرافية
العنوان: Minimum variance image blending for robust ultrasound image deconvolution
المؤلفون: Joo-young Kang, Jong Keun Song, Sung-Chan Park, Yun-Tae Kim, Kyuhong Kim, Jung-Ho Kim
المصدر: SPIE Proceedings.
بيانات النشر: SPIE, 2014.
سنة النشر: 2014
مصطلحات موضوعية: Blind deconvolution, Pixel, Computer science, Robustness (computer science), business.industry, Noise (signal processing), Wiener deconvolution, Image processing, Computer vision, Deconvolution, Artificial intelligence, business, Image restoration
الوصف: When the ultrasound wave propagates the human body, its velocity and attenuation change at each region, which make the PSF shape different. To solve the PSF estimation problem is ill-posed case and rarely error free which produces the PSF estimation errors and make the image overblurred by the sidelobe artifacts. For the commercialization of the ultrasound deconvolution method, the robustness of the image deconvolution without artifacts is essential. There exist many minimum variance beamformer algorithms. It is robust to noise and shows high resolution efficiently. We consider the channel data as image pixel and we present a new spatial varying MV (minimum variance) blending scheme with the deconvolved imageges in the image processing domain. With a stochastic image blending of the deconvolution images, we obtain high resolution results which suppress the blur artifacts enough although the input deconvolution images have restoration errors. We verify our algorithm on the real data. In all the case, we can observe that the artifacts are suppressed and show the highest resolution among the deconvolution methods.
تدمد: 0277-786X
DOI: 10.1117/12.2043905
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::ad92f7132723b21ecf06a793b87368f6
https://doi.org/10.1117/12.2043905
رقم الانضمام: edsair.doi...........ad92f7132723b21ecf06a793b87368f6
قاعدة البيانات: OpenAIRE
الوصف
تدمد:0277786X
DOI:10.1117/12.2043905