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Validation of image restoration methods on 3D-printed ultrasound phantoms

Abstract : Abstract: The resolution of ultrasound images is limited by the bandwidth of the imaging system and the features of the propagating medium. Using certain assumptions, image restoration can recover out-of-bandwidth data and improve resolution. Several resolution improvement methods have been reported in the literature. However, due to the lack of ground truth, their evaluation on experimental data remains an open issue. Indeed, to evaluate the performance of such methods, knowledge of the scattering function is necessary. Usually this is achieved with numerical simulations, since in traditional phantoms the exact distribution of scatterers is unknown. In the current work, based on a 3D-printed phantom, the feasibility of the evaluation of deconvolution is investigated. The deconvolution method used lp-norm-regularization terms with p=0.5 and p=2. Knowledge of the scattering function allows comparison of the deconvolved images with the ground truth. Thus, using the scattering function and the originally acquired B-mode image, performance of image restoration methods could be evaluated quantitatively through comparison of root mean square error and full width half maximum values. Preliminary results demonstrate the benefits of knowing the scattering function during experimental testing of image restoration methods. In summary, the current work shows the potential of an experimental method for evaluating the extent to which an image restoration method provides a faithful rendering of the underlying scattering structure.
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https://hal.archives-ouvertes.fr/hal-02777391
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Submitted on : Thursday, June 4, 2020 - 3:42:45 PM
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Long-term archiving on: : Thursday, December 3, 2020 - 1:30:13 PM

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Krisztián Füzesi, Adrian Basarab, György Cserey, Denis Kouamé, Miklós Gyöngy. Validation of image restoration methods on 3D-printed ultrasound phantoms. 2017 IEEE International Ultrasonics Symposium, Sep 2017, Washington, United States. pp.1-4, ⟨10.1109/ULTSYM.2017.8092120⟩. ⟨hal-02777391⟩

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