Image reconstruction of fluorescent molecular tomography based on the tree structured Schur complement decomposition.

Background: The inverse problem of fluorescent molecular tomography (FMT) often involves complex large-scale matrix operations, which may lead to unacceptable computational errors and complexity. In this research, a tree structured Schur complement decomposition strategy is proposed to accelerate th...

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Publicado en:BioMedical Engineering OnLine Vol. 9; pp. 20 - 21
Autores principales: Zou W, Wang J, Feng DD, Zou, Wei, Wang, Jiajun, Feng, David Dagan
Formato: research Journal Article
Publicado: BioMed Central 2010
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: BioMedical Engineering OnLine
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      dt: 2010
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      pub: BioMed Central
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        NLM20482886
        2010703523
        10.1186/1475-925X-9-20
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        105044829
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        atl: Image reconstruction of fluorescent molecular tomography based on the tree structured Schur complement decomposition.
      aug:
        au:
          Zou W
          Wang J
          Feng DD
          Zou, Wei
          Wang, Jiajun
          Feng, David Dagan
        affil: School of Electronics and Information Engineering, Soochow University, Suzhou 215021, China
      sug:
        subj:
          Image Processing, Computer Assisted Methods
          Tomography Methods
          Absorption
          Algorithms
          Finite Element Analysis
          Phantoms, Imaging
          Radiation
      ab: Background: The inverse problem of fluorescent molecular tomography (FMT) often involves complex large-scale matrix operations, which may lead to unacceptable computational errors and complexity. In this research, a tree structured Schur complement decomposition strategy is proposed to accelerate the reconstruction process and reduce the computational complexity. Additionally, an adaptive regularization scheme is developed to improve the ill-posedness of the inverse problem.Methods: The global system is decomposed level by level with the Schur complement system along two paths in the tree structure. The resultant subsystems are solved in combination with the biconjugate gradient method. The mesh for the inverse problem is generated incorporating the prior information. During the reconstruction, the regularization parameters are adaptive not only to the spatial variations but also to the variations of the objective function to tackle the ill-posed nature of the inverse problem.Results: Simulation results demonstrate that the strategy of the tree structured Schur complement decomposition obviously outperforms the previous methods, such as the conventional Conjugate-Gradient (CG) and the Schur CG methods, in both reconstruction accuracy and speed. As compared with the Tikhonov regularization method, the adaptive regularization scheme can significantly improve ill-posedness of the inverse problem.Conclusions: The methods proposed in this paper can significantly improve the reconstructed image quality of FMT and accelerate the reconstruction process.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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