Title
Performance Evaluation of a Priori Information on Reconstruction of Fluorescence Molecular Tomography
Abstract
Fluorescence molecular tomography (FMT) plays an important role in in vivo small animal imaging. However, due to the diffusive nature of photon propagation in biological tissues, FMT suffers from a low spatial resolution, which limits its capability of resolving the distribution of fluorescent biomarkers. In this paper, we investigate the effect of functional and structural a priori information on the accuracy of FMT reconstruction by a hybrid FMT and X-ray computed tomography imaging system. The results from numerical simulation and phantom experiments suggest that the fluorescence targets embedded in heterogeneous medium can be localized when structural a priori information is utilized to constrain the reconstruction process. In addition, both the functional and structural a priori information are essential for the recovery of fluorophore concentration.
Year
DOI
Venue
2015
10.1109/ACCESS.2015.2402673
IEEE Access
Keywords
Field
DocType
optical tomography,fmt reconstruction,photon propagation,computerised tomography,structural a priori information,biomedical optical imaging,image resolution,in vivo small animal imaging,spatial resolution,optical imaging,image reconstruction,reconstruction algorithms,fluorescence,functional a priori information,x-ray computed tomography imaging system,fluorescent biomarkers,fluorophore concentration,fluorescence molecular tomography,performance evaluation,biological tissues,phantoms,medical image processing,phantom,tomography,molecular imaging,in vivo,biomedical imaging
Biological system,Computer science,Medical imaging,Imaging phantom,A priori and a posteriori,Fluorophore,Artificial intelligence,Distributed computing,Iterative reconstruction,Computer vision,Molecular imaging,Tomography,Image resolution
Journal
Volume
ISSN
Citations 
3
2169-3536
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Xin Liu182.42
Zhuang-zhi Yan2148.28
Hongbing Lu332537.37