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A simulation study on the choice of regularization parameter in l2-norm ultrasound image restoration

Abstract : Ultrasound image deconvolution has been widely investigated in the literature. Among the existing approaches, the most common are based on ℓ2-norm regularization (or Tikhonov optimization) or the well-known Wiener filtering. However, the success of the Wiener filter in practical situations largely depends on the choice of the regularization hyperparameter. An appropriate choice is necessary to guarantee the balance between data fidelity and smoothness of the deconvolution result. In this paper, we revisit different approaches for automatically choosing this regularization parameter and compare them in the context of ultrasound image deconvolution via Wiener filtering. Two synthetic ultrasound images are used in order to compare the performances of the addressed methods.
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Submitted on : Monday, September 26, 2016 - 2:37:56 PM
Last modification on : Monday, July 4, 2022 - 9:31:28 AM


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  • HAL Id : hal-01371780, version 1
  • OATAO : 15324


Zhouye Chen, Adrian Basarab, Denis Kouamé. A simulation study on the choice of regularization parameter in l2-norm ultrasound image restoration. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015), Aug 2015, Milano, Italy. pp. 6346-6349. ⟨hal-01371780⟩



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