Pixel-wise reconstruction of tissue absorption coefficients in photoacoustic tomography using a non-segmentation iterative method

Shuangyang Zhang; Jiaming Liu; Zhichao Liang; Jia Ge; Yanqiu Feng; Wufan Chen; Li Qi

doi:10.1016/j.pacs.2022.100390

Pixel-wise reconstruction of tissue absorption coefficients in photoacoustic tomography using a non-segmentation iterative method

Photoacoustics. 2022 Aug 17:28:100390. doi: 10.1016/j.pacs.2022.100390. eCollection 2022 Dec.

Authors

Shuangyang Zhang^{1

2

3}, Jiaming Liu^{1

2

3}, Zhichao Liang^{1

2

3}, Jia Ge^{1

2

3}, Yanqiu Feng^{1

2

3}, Wufan Chen^{1

2

3}, Li Qi^{1

2

3}

Affiliations

¹ School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.
² Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China.
³ Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, Guangdong, China.

Abstract

In Photoacoustic Tomography (PAT), the acquired image represents a light energy deposition map of the imaging object. For quantitative imaging, the PAT image is converted into an absorption coefficient ( $μ_{a}$ ) map by dividing the light fluence (LF). Previous methods usually assume a uniform tissue $μ_{a}$ distribution, and consequently degrade the LF correction results. Here, we propose a simple method to reconstruct the pixel-wise $μ_{a}$ map. Our method is based on a non-segmentation-based iterative algorithm, which alternately optimizes the LF distribution and the $μ_{a}$ map. Using simulation data, as well as phantom and animal data, we implemented our algorithm and compared it to segmentation-based correction methods. The results show that our method can obtain accurate estimation of the LF distribution and therefore improve the image quality and feature visibility of the $μ_{a}$ map. Our method may facilitate efficient calculation of the concentration distributions of endogenous and exogenous agents in vivo.

Keywords: Absorption coefficient; Endogenous and exogenous agents; Photoacoustic Tomography; Quantitative imaging.