Title :
3D Compressed sensing ultrasound imaging
Author :
Quinsac, Céline ; Basarab, Adrian ; Kouamé, Denis ; Grégoire, Jean-Marc
Author_Institution :
IRIT, Univ. de Toulouse, Toulouse, France
Abstract :
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.
Keywords :
biomedical ultrasonics; conjugate gradient methods; image coding; image reconstruction; mean square error methods; medical image processing; sampling methods; 3D compressed sensing; 3D ultrasound imaging; US image k spaces; nonlinear conjugate gradient reconstruction algorithm; normalized root mean squared errors; undersampling patterns; Image coding; Image reconstruction; Imaging; Optimization; Radio frequency; Three dimensional displays; Transforms; 3D; compressed sensing; k-space; reconstruction; sparsity; ultrasound imaging;
Conference_Titel :
Ultrasonics Symposium (IUS), 2010 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-0382-9
DOI :
10.1109/ULTSYM.2010.5935479
