We used the ENVI algorithm, which allowed constrained unmixing to force the weights to sum to unity, making it easier to compare the separate images and threshold the data to classify pixels. It is a linear algebra problem to solve for the weighting matrix A, and the solution is usually obtained with an inverse least square procedure that minimizes the difference between the measured and modeled spectrum. Where R are the measured reference spectra. The LCTF permitted us to collect emission data in consecutive 5 nm steps between 450 and 625 nm, thus acting like a filter wheel with a very large number of filters, each of which has a high rejection ratioįor out-of-band transmission. 2 A liquid crystal tunable filter (LCTF), which can be tuned quickly to allow only a single, narrow wavelength range to pass, 3 was inserted into the optical path of a TPLSM in place of the normal barrier filter. Although there are a variety of approaches to obtaining an image cube, we employed a simple and straightforward modification of a technique developed at the Jet Propulsion Laboratory as part of a program to miniaturize imaging instruments for planetary spacecraft. 1 Here, we report the construction and use of an imaging spectrometer to acquire data from our fluorescent specimens as image cubes, three-dimensional data sets with two spatial dimensionsĪnd one wavelength dimension (λ). Imaging spectroscopy has been a major tool used to classify images derived from satellite and aircraft instruments. The difficulty of rapidly tuning the excitation wavelength in two-photon laser scanning microscopy (TPLSM), as well as the significant broadening of the excitation spectrum, makes the typical approach of selectively exciting different fluorochromes impractical and necessitates more advanced approaches. Although multilabel fluorescence microscopy has had an immense impact on research in several areas of biology, the advanced tools used elsewhere to perform multispectral analyses are rarely, if ever, applied.
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