Medical ultrasound image reconstruction using distributed compressive sampling

Author

Basarab, Adrian ; Liebgott, H. ; Bernard, O. ; Friboulet, D. ; Kouame, Denis

Author_Institution

IRIT, Univ. de Toulouse, Toulouse, France

fYear

2013

fDate

7-11 April 2013

Firstpage

628

Lastpage

631

Abstract

This paper investigates ultrasound (US) radiofrequency (RF) signal recovery using the distributed compressed sampling framework. The “correlation” between the RF signals forming a RF image is exploited by assuming that they have the same sparse support in the 1D Fourier transform, with different coefficient values. The method is evaluated using an experimental US image. The results obtained are shown to improve a previously proposed recovery method, where the correlation between RF signals was taken into account by assuming the 2D Fourier transform of the RF image sparse.

Keywords

Fourier transforms; biomedical ultrasonics; compressed sensing; image reconstruction; medical image processing; ultrasonic imaging; 1D Fourier transform; 2D Fourier transform; RF image sparse; RF signal correlation; US imaging; distributed compressed sampling framework; distributed compressive sampling; medical ultrasound image reconstruction; sparse support; ultrasound radiofrequency signal recovery; Fourier transforms; Image reconstruction; Imaging; RF signals; Radio frequency; Ultrasonic imaging; Vectors; Fourier transform; compressive sampling; jointly sparse signal; radiofrequency signals; ultrasound imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on

Conference_Location

San Francisco, CA

ISSN

1945-7928

Print_ISBN

978-1-4673-6456-0

Type

conf

DOI

10.1109/ISBI.2013.6556553

Filename

6556553