| dc.description.abstract | Fluorescence lifetime imaging microscopy (FLIM) is a noninvasive invasive optical imaging modality which is finding new applications in medical imaging. In FLIM, the fluorescence time decay is measured at a pixel. The fluorescence impulse response function (IRF) is then estimated using a deconvolution of the instrument response and the measured fluorescence time decay. Two of the challenges facing FLIM are speed of the deconvolution and the accuracy of the IRFs.
The linear expansion of the fluorescence decays based on the orthonormal Laguerre basis functions (LBFs) is among the fastest methods for estimating the IRFs. The automated implementation to optimize the Laguerre parameter improves the speed of the deconvolution using the LBFs but uses a global optimization. Therefore, the IRFs do not necessarily mimic exponential time decays, or monotonically decreasing functions. On the other hand, applying a constraint to the LBFs using the Active Set Nonnegative Least Squares (NNLS) method improves the IRF estimation. The estimation of the Laguerre parameter using the NNLS method, however, is about 10-15x slower. By combining these two deconvolution techniques, we found that the deconvolution time is similar to the automated global Laguerre parameter deconvolution while the IRF estimation always results in a monotonically decreasing function. | en |
