Accounting for filter bandwidth improves the quantitative accuracy of bioluminescence tomography.
Bioluminescence imaging is a noninvasive technique whereby surface weighted images of luminescent probes within animals are used to characterize cell count and function. Traditionally, data are collected over the entire emission spectrum of the source using no filters and are used to evaluate cell count/function over the entire spectrum. Alternatively, multispectral data over several wavelengths can be incorporated to perform tomographic reconstruction of source location and intensity. However, bandpass filters used for multispectral data acquisition have a specific bandwidth, which is ignored in the reconstruction. In this work, ignoring the bandwidth is shown to introduce a dependence of the recovered source intensity on the bandwidth of the filters. A method of accounting for the bandwidth of filters used during multispectral data acquisition is presented and its efficacy in increasing the quantitative accuracy of bioluminescence tomography is demonstrated through simulation and experiment. It is demonstrated that while using filters with a large bandwidth can dramatically decrease the data acquisition time, if not accounted for, errors of up to 200% in quantitative accuracy are introduced in two-dimensional planar imaging, even after normalization. For tomographic imaging, the use of this method to account for filter bandwidth dramatically improves the quantitative accuracy.
University of Birmingham, PSIBS Doctoral Training Centre, Edgbaston, Birmingham B15 2TT, United KingdombUniversity of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom.
Shelley L
SL
Taylor
University of Birmingham, PSIBS Doctoral Training Centre, Edgbaston, Birmingham B15 2TT, United KingdombUniversity of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom.
Suzannah K G
SK
Mason
University of Birmingham, PSIBS Doctoral Training Centre, Edgbaston, Birmingham B15 2TT, United KingdombUniversity of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom.
Sophie L
SL
Glinton
University of Birmingham, College of Medical and Dental Sciences, School of Immunity and Infection, Edgbaston, Birmingham B15 2TT, United Kingdom.
Mark
M
Cobbold
University of Birmingham, PSIBS Doctoral Training Centre, Edgbaston, Birmingham B15 2TT, United KingdombUniversity of Birmingham, School of Computer Science, Edgbaston, Birmingham B15 2TT, United Kingdom.
Hamid
H
Dehghani
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D041622:Tomography, Optical / Q000379:methods*