3D compressed sensing ultrasound imaging

Céline Quinsac (1) , Adrian Basarab (1, 2) , Jean-Marc Grégoire (3) , Denis Kouamé (1)

1 IRIT-TCI - Traitement et Compréhension d’Images
2 UT3 - Université Toulouse III - Paul Sabatier
3 iBraiN - Imaging, Brain & Neuropsychiatry

This paper proposes a compressed sensing method adapted to 3D ultrasound (US) imaging. Three undersampling patterns suited for 3D US imaging, together with a nonlinear conjugate gradient reconstruction algorithm of the US image k spaces, are investigated in vivo radio-frequency 3D US volumes. Reconstructions from 50% of the samples of the original 3D volume show little information loss in terms of normalized root mean squared errors.

Mots clés: ultrasound imaging; compressed sensing; reconstruction; 3D; k-space; sparsity

Domaines: Traitement du signal et de l'image [eess.SP]

Céline Quinsac, Adrian Basarab, Jean-Marc Grégoire, Denis Kouamé. 3D compressed sensing ultrasound imaging. IEEE International Ultrasonics Symposium (IUS 2010), IEEE UFFC: IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society, Oct 2010, San Diego, CA, United States. pp.363--366, ⟨10.1109/ULTSYM.2010.5935479⟩. ⟨hal-03146739⟩