Nonlocal means-based speckle filtering for ultrasound images.

Pierrick Coupé 1 Pierre Hellier 1, * Charles Kervrann 2, 3 Christian Barillot 1
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
3 VISTAS - Spatio-Temporal Vision and Learning
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the nonlocal (NL)-means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image.
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Pierrick Coupé, Pierre Hellier, Charles Kervrann, Christian Barillot. Nonlocal means-based speckle filtering for ultrasound images.. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2009, 18 (10), pp.2221-9. ⟨10.1109/TIP.2009.2024064⟩. ⟨inserm-00428524v2⟩

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