IEEE transactions on bio-medical engineering(2020)
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摘要
Objective:
Fluorescence molecular tomography (FMT) can provide valuable molecular information by mapping the bio-distribution of fluorescent reporter molecules in the intact organism. Various prototype FMT systems have been introduced during the past decade. However, none of them has evolved as a standard tool for routine biomedical research. The goal of this paper is to develop a software package that can automate the complete FMT reconstruction procedure.
Methods:
We present smart toolkit for fluorescence tomography (STIFT), a comprehensive platform comprising three major protocols: 1) virtual FMT, i.e., forward modeling and reconstruction of simulated data; 2) control of actual FMT data acquisition; and 3) reconstruction of experimental FMT data.
Results:
Both simulation and phantom experiments have shown robust reconstruction results for homogeneous and heterogeneous tissue-mimicking phantoms containing fluorescent inclusions.
Conclusion:
STIFT can be used for optimization of FMT experiments, in particular for optimizing illumination patterns.
Significance:
This paper facilitates FMT experiments by bridging the gaps between simulation, actual experiments, and data reconstruction.
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关键词
Fluorescence tomography,finite element modeling,image reconstruction,optimization,validation