Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography.
We investigate fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography for applications in small animal imaging. Our forward model uses a diffusion approximation for optically inhomogeneous tissue, which we solve using a finite element method (FEM). We examine two approaches to incorporating the forward model into the solution of the inverse problem. In a conventional direct calculation approach one computes the full forward model by repeated solution of the FEM problem, once for each potential source location. We describe an alternative on-the-fly approach where one does not explicitly solve for the full forward model. Instead, the solution to the forward problem is included implicitly in the formulation of the inverse problem, and the FEM problem is solved at each iteration for the current image estimate. We evaluate the convergence speeds of several representative iterative algorithms. We compare the computation cost of those two approaches, concluding that the on-the-fly approach can lead to substantial reductions in total cost when combined with a rapidly converging iterative algorithm.
Ahn
Sangtae
S
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA.
Chaudhari
Abhijit J
AJ
Darvas
Felix
F
Bouman
Charles A
CA
Leahy
Richard M
RM
D000465:Algorithms; D000818:Animals; D001932:Brain Neoplasms / Q000000981:diagnostic imaging; D005453:Fluorescence; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016018:Least-Squares Analysis; D049449:Luminescence; D051379:Mice; D015203:Reproducibility of Results; D013997:Time Factors; D041622:Tomography, Optical / Q000379:methods*; D014057:Tomography, X-Ray Computed