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

The reconstruction of bioluminescence tomography (BLT) is severely ill-posed due to the insufficient measurements and diffuses nature of the light propagation. Predefined permissible source region (PSR) combined with regularization terms is one common strategy to reduce such ill-posedness. However,...

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Publicado en:Medical & Biological Engineering & Computing Vol. 56; no. 11; pp. 2067 - 2082
Autores principales: Yang, Defu, Wang, Lin, Chen, Dongmei, Yan, Chenggang, He, Xiaowei, Liang, Jimin, Chen, Xueli
Formato: Journal Article
Publicado: Springer Nature Nov2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2018
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      pub: Springer Nature
      place: New York, New York
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        atl: Filtered maximum likelihood expectation maximization based global reconstruction for bioluminescence tomography.
      aug:
        au:
          Yang, Defu
          Wang, Lin
          Chen, Dongmei
          Yan, Chenggang
          He, Xiaowei
          Liang, Jimin
          Chen, Xueli
        affil: Institute of Information and Control, Hangzhou Dianzi University, 310018, Hangzhou, China
      sug:
        subj:
          Image Interpretation, Computer Assisted Methods
          Luminescent Measurements Methods
          Tomography, Optical Methods
          Algorithms
          Animals
          Liver Neoplasms
          Mice
          Male
          Scales
          Male
      ab: The reconstruction of bioluminescence tomography (BLT) is severely ill-posed due to the insufficient measurements and diffuses nature of the light propagation. Predefined permissible source region (PSR) combined with regularization terms is one common strategy to reduce such ill-posedness. However, the region of PSR is usually hard to determine and can be easily affected by subjective consciousness. Hence, we theoretically developed a filtered maximum likelihood expectation maximization (fMLEM) method for BLT. Our method can avoid predefining the PSR and provide a robust and accurate result for global reconstruction. In the method, the simplified spherical harmonics approximation (SPN) was applied to characterize diffuse light propagation in medium, and the statistical estimation-based MLEM algorithm combined with a filter function was used to solve the inverse problem. We systematically demonstrated the performance of our method by the regular geometry- and digital mouse-based simulations and a liver cancer-based in vivo experiment. Graphical abstract The filtered MLEM-based global reconstruction method for BLT.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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