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- W2058001024 abstract "Reconstruction of the bioluminescent source information in small animals in vivo is the inverse problem of Bioluminescence tomography (BLT), which is proved severely ill-posed. Regularization plays an important role in BLT, and choosing the right amount of regularization is crucial to get a meaningful result. However, automated methods to choose a regularization parameter have not been sufficiently considered to date. In this paper, we present an adaptive parameter selection method and compare it with three existing methods: L-Curve Generalized cross-validation (GCV), and Normalized Cumulative Periodogram (NCP). The proposed method was validated by numerical simulation of a heterogeneous phantom experiment. The reconstructed results suggest that the adaptive parameter choosing method perform best and combined with Tikhonov regularization it can achieve accurate localization of bioluminescent source." @default.
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- W2058001024 date "2010-10-01" @default.
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- W2058001024 title "Adaptive parameter selection for Tikhonov regularization in Bioluminescence tomography" @default.
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- W2058001024 doi "https://doi.org/10.1109/bmei.2010.5639653" @default.
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