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Communication Dans Un Congrès Année : 2020

Blind deconvolution of fundamental and harmonic ultrasound images

Résumé

Restoring the tissue reflectivity function (TRF) from ultrasound (US) images is an extensively explored research field. It is well-known that human tissues and contrast agents have a non-linear behavior when interacting with US waves. In this work, we investigate this non-linearity and the interest of including harmonic US images in the TRF restoration process. Therefore, we introduce a new US image restoration method taking advantage of the fundamental and harmonic components of the observed radiofrequency (RF) image. The depth information contained in the fundamental component and the good resolution of the harmonic image are combined to create an image with better properties than the fundamental and harmonic images considered separately. Under the hypothesis of weak scattering, the RF image is modeled as the 2D convolution between the TRF and the system point spread function (PSF). An inverse problem is formulated based on this model able to jointly estimate the TRF and the PSF. The interest of the proposed blind deconvolution algorithm is shown through an in vivo result and compared to a conventional US restoration method.
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Dates et versions

hal-02942314 , version 1 (17-09-2020)

Identifiants

  • HAL Id : hal-02942314 , version 1
  • OATAO : 26324

Citer

Mohamad Hourani, Adrian Basarab, Oleg Michailovich, Giulia Matrone, Alessandro Ramalli, et al.. Blind deconvolution of fundamental and harmonic ultrasound images. 17th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2020), Apr 2020, Iowa City, United States. pp.854. ⟨hal-02942314⟩
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