Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm.

Content Provider	Semantic Scholar
Author	Song, Xiaolei Wang, Daifa Chen, Nanguang Bai, Jing Wang, Hongkai
Copyright Year	2007
Abstract	With the development of in-vivo free-space fluorescence molecular imaging and multi-modality imaging for small animals, there is a need for new reconstruction methods for real animal-shape models with a large dataset. In this paper we are reporting a novel hybrid adaptive finite element algorithm for fluorescence tomography reconstruction, based on a linear scheme. Two different inversion strategies (Conjugate Gradient and Landweber iterations) are separately applied to the first mesh level and the succeeding levels. The new algorithm was validated by numerical simulations of a 3-D mouse atlas, based on the latest free-space setup of fluorescence tomography with 360 degrees geometry projections. The reconstructed results suggest that we are able to achieve high computational efficiency and spatial resolution for models with irregular shape and inhomogeneous optical properties.
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Alternate Webpage(s)	https://www.researchgate.net/profile/Nanguang_Chen/publication/26315555_Reconstruction_for_free-space_fluorescence_tomography_using_a_novel_hybrid_adaptive_finite_element_algorithm/links/09e415120b16991c8d000000.pdf
PubMed reference number	19551128v1
Volume Number	15
Issue Number	26
Journal	Optics express
Language	English
Access Restriction	Open
Subject Keyword	Atlases Fluorescence Molecular Imaging Numerous Preparation Projections and Predictions Silo (dataset) algorithm tomography
Content Type	Text
Resource Type	Article