Abstract：
:It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.
journal_name
Phys Med Bioljournal_title
Physics in medicine and biologyauthors
Pu H,Zhang G,He W,Liu F,Guang H,Zhang Y,Bai J,Luo Jdoi
10.1088/0031-9155/59/17/5025subject
Has Abstractpub_date
2014-09-07 00:00:00pages
5025-42issue
17eissn
0031-9155issn
1361-6560journal_volume
59pub_type
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