Liu, Yan and Chuah, Jonathan and Huang, Yishu and Stiel, Andre C. and Unser, Michael and Dong, Jonathan (2025) Model-based temporal unmixing towards quantitative photo-switching optoacoustic tomography. OPTICS EXPRESS, 33 (3). pp. 6216-6227. ISSN 1094-4087
Full text not available from this repository. (Request a copy)Abstract
Optoacoustic (OA) imaging combined with reversibly photoswitchable proteins has emerged as a promising technology for the high-sensitivity and multiplexed imaging of cells in live tissues in preclinical research. Through carefully designed illumination schedules of ON and OFF laser pulses, the resulting OA signal is a multiplex of different reporter species and the background. We propose a model-based variational framework to computationally unmix and image different species of photo-switching reporters using optoacoustic tomography. It is based on a detailed mathematical description of the photo-switching mechanism, which models how relevant physical parameters such as the kinetic constants and light fluence impact the switching signal. We introduce an algorithm that operates on images, as opposed to traditional pixelwise approaches. It takes the form of an iterative inversion combined with tailored & ell;1 and total-variation regularization to increase the robustness to noise and to improve the unmixing quality. We show that our method can disentangle multiple spatially overlapping labels and recover continuous maps of quantities of interest on controlled phantoms and mice experiments. (c) 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | PHOTOACOUSTIC TOMOGRAPHY; PRACTICAL GUIDE; ALGORITHM |
| Subjects: | 500 Science > 540 Chemistry & allied sciences 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 14 Jul 2026 08:56 |
| Last Modified: | 14 Jul 2026 08:56 |
| URI: | https://pred.uni-regensburg.de/id/eprint/66968 |
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