### Abstract

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.

Original language | English (US) |
---|---|

Pages (from-to) | 3921-3942 |

Number of pages | 22 |

Journal | Physics in Medicine and Biology |

Volume | 53 |

Issue number | 14 |

DOIs | |

State | Published - Jul 21 2008 |

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### ASJC Scopus subject areas

- Biomedical Engineering
- Physics and Astronomy (miscellaneous)
- Radiology Nuclear Medicine and imaging
- Radiological and Ultrasound Technology

### Cite this

*Physics in Medicine and Biology*,

*53*(14), 3921-3942. https://doi.org/10.1088/0031-9155/53/14/013

**Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography.** / Ahn, Sangtae; Chaudhari, Abhijit; Darvas, Felix; Bouman, Charles A.; Leahy, Richard M.

Research output: Contribution to journal › Article

*Physics in Medicine and Biology*, vol. 53, no. 14, pp. 3921-3942. https://doi.org/10.1088/0031-9155/53/14/013

}

TY - JOUR

T1 - Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography

AU - Ahn, Sangtae

AU - Chaudhari, Abhijit

AU - Darvas, Felix

AU - Bouman, Charles A.

AU - Leahy, Richard M.

PY - 2008/7/21

Y1 - 2008/7/21

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=47649130211&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=47649130211&partnerID=8YFLogxK

U2 - 10.1088/0031-9155/53/14/013

DO - 10.1088/0031-9155/53/14/013

M3 - Article

C2 - 18591735

AN - SCOPUS:47649130211

VL - 53

SP - 3921

EP - 3942

JO - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

IS - 14

ER -