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Filtered maximum likelihood expectation maximization based global reconstruction for bioluminescence tomography.

Defu Yang1, Lin Wang2, Dongmei Chen3

  • 1Institute of Information and Control, Hangzhou Dianzi University, Hangzhou, 310018, China.

Medical & Biological Engineering & Computing
|May 18, 2018
PubMed
Summary

This study introduces a new filtered maximum likelihood expectation maximization (fMLEM) method for bioluminescence tomography (BLT). The fMLEM approach enhances global reconstruction accuracy by avoiding subjective permissible source region (PSR) definition.

Keywords:
Bioluminescence tomographyGlobal reconstructionImage reconstruction technique

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Area of Science:

  • Biomedical Imaging
  • Medical Physics
  • Optical Tomography

Background:

  • Bioluminescence tomography (BLT) reconstruction is challenging due to ill-posed inverse problems.
  • Traditional methods often rely on predefined permissible source regions (PSRs), which are subjective and difficult to determine accurately.
  • Diffuse light propagation in biological tissues complicates accurate source localization.

Purpose of the Study:

  • To develop a novel, theoretically grounded method for robust and accurate global bioluminescence tomography reconstruction.
  • To overcome the limitations of predefined permissible source regions (PSRs) in BLT.
  • To improve the accuracy of quantitative bioluminescence imaging.

Main Methods:

  • Developed a filtered maximum likelihood expectation maximization (fMLEM) algorithm for BLT.
  • Utilized the simplified spherical harmonics approximation (SPN) to model diffuse light propagation.
  • Employed a statistical estimation-based MLEM algorithm integrated with a filter function to solve the inverse problem.

Main Results:

  • The fMLEM method demonstrated robust and accurate global reconstruction without requiring predefined permissible source regions (PSRs).
  • Simulations using regular geometries and digital mice validated the method's performance.
  • In vivo experiments on liver cancer models confirmed the practical applicability and accuracy of the fMLEM approach.

Conclusions:

  • The proposed filtered maximum likelihood expectation maximization (fMLEM) method offers a significant advancement for bioluminescence tomography (BLT).
  • This approach provides accurate global reconstruction, eliminating the need for subjective permissible source region (PSR) definition.
  • The fMLEM method shows strong potential for various preclinical and clinical applications requiring precise bioluminescence imaging.