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Block-Wise 3D Ultrasound Image Super-Resolution

Abstract : This paper addresses the problem of 3D ultrasound (US) single image super-resolution (SR), i.e., recover a high-resolution volume from its blurred, decimated, and noisy version. A new 3D US SR technique based on a linear forward model is studied by taking into account the axial variability of the point spread function (PSF) within a block-wise recovery process. The PSF is estimated using a recent algorithm along the axial direction with the assumption that it is isotropic in the other two spatial directions. By exploiting the linear image formation model, a cost function is constructed from a data fidelity term penalized by an $l_1$-norm regularization function imposing the sparsity of the solution. Numerical results show the efficiency of the proposed method when compared to the observed image.
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Submitted on : Monday, September 20, 2021 - 2:37:06 PM
Last modification on : Wednesday, January 12, 2022 - 8:02:37 PM
Long-term archiving on: : Tuesday, December 21, 2021 - 6:53:18 PM


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  • HAL Id : hal-03349339, version 1


Kenule Tuador Nwigbo, Duong-Hung Pham, François Varray, Adrian Basarab, Denis Kouamé. Block-Wise 3D Ultrasound Image Super-Resolution. IEEE International Ultrasonics Symposium (IUS 2021), Sep 2021, Xi’an (virtual conference), China. pp.1-4. ⟨hal-03349339⟩



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