Research on the underdetermined problem in 3D fluorescence imaging based on compressive sensing
WANG Zhangli
CHEN Chunxiao
LU Xiong
LI Dongsheng
Abstract：The idea of compressive sensing theory makes it possible to reconstruct the tumors of animals in 3D fluorescence molecu-lar tomography.However, the column vectors of the coefficient matrix used for 3D FMT reconstruction are highly coherent, which means the sparsest solution of the regularization of is not available.In this paper,we proposed a method to reduce the coherence of co-efficient matrix based on QR-Decomposition,and realized reverse reconstruction by solving the problem of regularization.We investi-gated the performance of the proposed method with both simulated data and in vivo mice experimental data.The results demonstrate that the proposed method can effectively reduce the uncertainty of the tumor reverse reconstruction and improve the reconstruction accuracy.
Keywords：UnderdeterminedCompression sensingQR-DecompositionL1regularizationL1/2regularizationSparse recon-struction
Publication Date：2018-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：5( 66-70 )