Singular Value Decomposition-based Analysis on Fluorescence Molecular Tomography in the Mouse Atlas

The application of CCD camera improves the quality of fluorescence molecular tomography (FMT). However, large size of data set offered by CCD might increase the computational burden in the reconstruction. To balance the data size and reconstruction quality, singular value decomposition (SVD)-based analysis is applied. Simulation is performed with mouse atlas. By observing the relative gain of number of effective SVD components and reconstruction results, we find that the minimum field of view can be obtained for each projection in order to realize the optimization of experimental setup and furthest utilize data set.