Ultrasound spatiotemporal despeckling via Kronecker wavelet-Fisz thresholding

Younes Farouj (1, 2) , Laurent Navarro (3) , Jean-Marc Freyermuth (4) , Marianne Clausel (5) , Philippe Delachartre (6)

1 UNIGE - Université de Genève = University of Geneva
2 EPFL - Ecole Polytechnique Fédérale de Lausanne
3 SAINBIOSE - Santé Ingénierie Biologie Saint-Etienne
4 UNINE - Université de Neuchâtel = University of Neuchatel
5 DAO - Données, Apprentissage et Optimisation
6 Imagerie Ultrasonore

We propose a novel framework for despeckling ultrasound image sequences while respecting the structural details. More precisely, we use thresholding in an adapted wavelet domain that jointly takes into account for the non-Gaussian statistics of the noise and the differences in spatial and temporal regularities. The spatiotemporal wavelet is obtained via the Kronecker product of two sparsifying wavelet bases acting, respectively, on the spatial and temporal domains. Besides enabling a structured sparse representation of the time–space plan, it also makes it possible to perform a variance stabilization routine on the spatial domain through a Fisz transformation. The proposed method enjoys adaptability, easy tuning and theoretical guaranties. We propose the corresponding algorithm together with results that demonstrate the benefits of the proposed spatiotemporal approach over the successive spatial treatment. Finally, we describe a data-driven extension of the proposed method that is based on temporal pre-filtering.

Mots clés: Dynamic ultrasound imaging; Despeckling; Fisz transformation; Variance stabilization; Structured sparsity

Domaines: Acoustique [physics.class-ph]; Imagerie médicale; Traitement du signal et de l'image [eess.SP]

Younes Farouj, Laurent Navarro, Jean-Marc Freyermuth, Marianne Clausel, Philippe Delachartre. Ultrasound spatiotemporal despeckling via Kronecker wavelet-Fisz thresholding. Signal, Image and Video Processing, 2018, 12 (6), pp.1125 - 1132. ⟨10.1007/s11760-018-1260-6⟩. ⟨hal-01912719⟩