(see Instrument response function (IRF/prompt))). Instrument Response: The dataset that contains the instrument response. LMA: The Levenberg-Marquardt algorithm.Algorithm: The algorithm used for fitting.Noise Model: The noise model used for fitting (see Noise models). If the results are satisfactory, the LM algorithm will terminate. The LM algorithm checks at the end of each iteration whether the fit is good enough by comparing \(\chi^2\) with this threshold. Χ² Target: The \(\chi^2\) value below which the LM fitting will stop. Left to right: Intensity of dataset after binning of radius 0, 1, and 2. The binning of the dataset is performed by convolving the dataset with this kernel, which is equivalent to adding neighboring pixels into the center: Kernel Size: The radius (in pixels, excluding the center) of the binning kernel.įLIMJ plugin currently only supports the square kernel with size \(2r+1\) and values all equal to 1 where \(r\) is the radius). For those pixels, all parameters are treated as 0 both when being previewed and when the whole dataset is fitted. When selected for preview in the Preview panel, only the photon counts (orange dots) will be plotted. Intensity Thresh.: The minimal pixel intensity to be fitted.Īny pixel with cumulative intensity (over all time bins) below this threshold will be skipped when the dataset is fitted. Sometimes you may want to fine-tune the fitting configurations. \(\chi^2\) shows the chi-squared measure of the fit (see Noise models).\(z, A, \tau\) (or \(z_1, A_1, A_2, \tau_1, \tau_2\) in two-component fit) are the background, initial intensity and lifetime parameters of the model.Photon Count displays the total number of photons collected between the start and end cursor.Orange dots denote the photon counts in each time bin in Fit plot and denote the residual (\(y_\)) in Res plot.Red curve denotes the fitted portion of decay between the start and end cursor.X and Y are coordinates of the pixel cursor counting from the upper left corner. If the dataset comes with a (fourth) spectral dimension, the user has to choose the spectral channel to analyze as well:īefore fitting the entire dataset, the user may click on the intensity image or type in the coordinates in Preview panel to preview the fitted curve and parameters of the pixel under the cursor: Otherwise, the user may be asked to provide the information: sdt), the dataset likely has metadata attached, which helps FLIM plugin infer the order of the X, Y, and T axes as well as the time bin size. If the dataset is opened from a file supported by SCIFIO (such as a. With the desired dataset window active, launch FLIMJ from the menu under Analyze › Lifetime › FLIMJ or search for “FLIMJ” in the search box:įLIMJ plugin accepts only 3- or 4-dimensional datasets. Open a dataset (such as this one) or select an existing image display in Fiji: Once you have installed the FLIMJ plugin, it becomes available on the menu under Analyze › Lifetime › FLIMJ. The FLIMJ plugin is available from the “FLIMJ” update site.
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