Comput Math Methods Med - Hybrid multilevel sparse reconstruction for a whole domain bioluminescence tomography using adaptive finite element.

Tópicos

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Resumo

Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed with in vivo experiments.

Resumo Limpo

quantit reconstruct bioluminesc sourc boundari measur challeng illpos invers problem owe high degre absorpt scatter light tissu present hybrid multilevel reconstruct scheme combin abil spars regular advantag adapt finit element method view characterist differ discret level two differ invers algorithm employ initi coars mesh succeed one strike balanc stabil effici numer experi result digit mous model demonstr propos scheme can accur local quantifi sourc distribut maintain reconstruct stabil comput economi effect hybrid reconstruct scheme confirm vivo experi

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