Compressive sampling in photo-acoustic imaging

Jean Provost; Frédéric Lesage

doi:10.1117/12.779123

8 November 2007 Compressive sampling in photo-acoustic imaging

Jean Provost, Frédéric Lesage

Author Affiliations +

Proceedings Volume 6796, Photonics North 2007; 67960K (2007) https://doi.org/10.1117/12.779123
Event: Photonics North 2007, 2007, Ottawa, Canada

Abstract

Photo-acoustic (PA) imaging has been developped for different purposes but recent years has seen the technique gain interest with applications to small animal imaging. As a technique it is sensitive to endogenous optical contrast present in tissues and, contrary to diffuse optical imaging, it promises to bring high resolution imaging for in vivo studies at mid-range depths (3mm-10mm). However, a typical acquisition for the reconstruction of one slice in PA tomography can take up to approximatively 30 minutes which is clearly prohibitive for 3D imaging. This paper suggests a new reconstruction strategy using the compressive sampling formalism which states that a small number of linear projection of a compressible image contains enough information for reconstruction. This new scheme allows perfect reconstruction of numerical phantoms with only a fraction of the measurements normally needed with classical methods such as the pseudo-inverse.

Citation Download Citation

Jean Provost and Frédéric Lesage "Compressive sampling in photo-acoustic imaging", Proc. SPIE 6796, Photonics North 2007, 67960K (8 November 2007); https://doi.org/10.1117/12.779123

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE