TY - JOUR
T1 - Full-Wave Image Reconstruction in Transcranial Photoacoustic Computed Tomography Using a Finite Element Method
AU - Luo, Yilin
AU - Huang, Hsuan Kai
AU - Sastry, Karteekeya
AU - Hu, Peng
AU - Tong, Xin
AU - Kuo, Joseph
AU - Aborahama, Yousuf
AU - Na, Shuai
AU - Villa, Umberto
AU - Anastasio, Mark A.
AU - Wang, Lihong V.
N1 - This work was sponsored by the United States National Institutes of Health (NIH) grants U01 EB029823, R35 CA220436 (Outstanding Investigator Award), and R01 EB028277. (Corresponding author: Lihong V. Wang.) Y. L., K. S., P. H., X. T., Y. A. and L. V. W. are with the Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering and the Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125 USA (e-mail: [email protected]; [email protected]).
PY - 2025
Y1 - 2025
N2 - Transcranial photoacoustic computed tomography presents challenges in human brain imaging due to skull-induced acoustic aberration. Existing full-wave image reconstruction methods rely on a unified elastic wave equa- tion for skull shear and longitudinal wave propagation, therefore demanding substantial computational resources. We propose an efficient discrete imaging model based on finite element discretization. The elastic wave equation for solids is solely applied to the hard-tissue skull region, while the soft-tissue or coupling-medium region that dominates the simulation domain is modeled with the simpler acoustic wave equation for liquids. The solid-liquid interfaces are explicitly modeled with elastic-acoustic coupling. Furthermore, finite element discretization allows coarser, irregular meshes to conform to object geometry. These factors significantly reduce the linear system size by 20 times to facilitate accurate whole-brain simulations with improved speed. We derive a matched forward-adjoint operator pair based on the model to enable integration with various optimization algorithms. We validate the reconstruction framework through numerical simulations and phantom experiments.
AB - Transcranial photoacoustic computed tomography presents challenges in human brain imaging due to skull-induced acoustic aberration. Existing full-wave image reconstruction methods rely on a unified elastic wave equa- tion for skull shear and longitudinal wave propagation, therefore demanding substantial computational resources. We propose an efficient discrete imaging model based on finite element discretization. The elastic wave equation for solids is solely applied to the hard-tissue skull region, while the soft-tissue or coupling-medium region that dominates the simulation domain is modeled with the simpler acoustic wave equation for liquids. The solid-liquid interfaces are explicitly modeled with elastic-acoustic coupling. Furthermore, finite element discretization allows coarser, irregular meshes to conform to object geometry. These factors significantly reduce the linear system size by 20 times to facilitate accurate whole-brain simulations with improved speed. We derive a matched forward-adjoint operator pair based on the model to enable integration with various optimization algorithms. We validate the reconstruction framework through numerical simulations and phantom experiments.
KW - Domain decomposition
KW - acoustic-elastic coupling
KW - finite element method
KW - full-wave reconstruction
KW - photoacoustic tomography
KW - skull deaberration
KW - transcranial imaging
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U2 - 10.1109/TMI.2024.3456595
DO - 10.1109/TMI.2024.3456595
M3 - Article
C2 - 39250376
AN - SCOPUS:85204154615
SN - 0278-0062
VL - 44
SP - 645
EP - 655
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 2
ER -