Local nonlinear spectral unmixing for oxygen saturation imaging using photoacoustic computed tomography

Cheng Ma; Manxiu Cui

doi:10.1117/12.3009037

13 March 2024 Local nonlinear spectral unmixing for oxygen saturation imaging using photoacoustic computed tomography

Cheng Ma, Manxiu Cui

Proceedings Volume PC12842, Photons Plus Ultrasound: Imaging and Sensing 2024; PC128421H (2024) https://doi.org/10.1117/12.3009037
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Multispectral photoacoustic tomography (PAT) offers high-resolution images of deep tissue oxygen saturation (sO2), but the complexity of photon absorption and scattering affects sO2 accuracy. This study applied a rigorous light transport model, revealing that PA spectra within biological tissue can be represented as convex cones (CCs) in a high-dimensional space. Using the CC model, sO2 can be estimated by finding the nearest CC to measured data, even in noisy conditions. This method combines a physical model with machine learning, demonstrating practicality and robustness in numerical, phantom, and in vivo imaging experiments, with an average sO2 estimation error of just 3% in human trials. Additionally, it outperforms clinical practices like linear spectral unmixing, suggesting broader applications in PA molecular imaging and diffuse optical imaging.

Conference Presentation

Citation Download Citation

Cheng Ma and Manxiu Cui "Local nonlinear spectral unmixing for oxygen saturation imaging using photoacoustic computed tomography", Proc. SPIE PC12842, Photons Plus Ultrasound: Imaging and Sensing 2024, PC128421H (13 March 2024); https://doi.org/10.1117/12.3009037

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