Sparse signal representation at the service of quantitative optoacoustic tomography

Amir Rosenthal; Daniel Razansky; Vasilis Ntziachristos

doi:10.1117/12.843264

23 February 2010 Sparse signal representation at the service of quantitative optoacoustic tomography

Amir Rosenthal, Daniel Razansky, Vasilis Ntziachristos

Proceedings Volume 7564, Photons Plus Ultrasound: Imaging and Sensing 2010; 75640S (2010) https://doi.org/10.1117/12.843264
Event: SPIE BiOS, 2010, San Francisco, California, United States

Abstract

We report on a new method for extraction of quantified optical absorption maps of scattering and absorbing media using sparse representation, a relatively recent and fast emerging technique in the field of signal processing. The tomographic reconstruction is facilitated by assuming slow spatial variations of illuminating optical field along with relatively sharp changes in optical absorption coefficient. As opposed to previous approaches that utilize photon transport equation in order to correct images for inhomogeneous light distribution within the imaged object, the method herein provides an estimate for photon fluence directly from the recorded optoacoustic signals. In this way a robust quantitative performance is achieved without prior knowledge of illumination geometry and optical properties of the object.

Citation Download Citation

Amir Rosenthal, Daniel Razansky, and Vasilis Ntziachristos "Sparse signal representation at the service of quantitative optoacoustic tomography", Proc. SPIE 7564, Photons Plus Ultrasound: Imaging and Sensing 2010, 75640S (23 February 2010); https://doi.org/10.1117/12.843264

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

Includes PDF, HTML & Video, when available