Parameter

Description

Algorithm

Selects the Apotome deconvolution algorithm.

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Fast Iterative (Joint)

Uses an algorithm based on Deconvolution methods for structured illumination microscopy, with some enhancements as described in the technical note. It is faster and less memory intensive, and also purely using the image formation model.

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Constraint Iterative (Joint)

Uses an algorithm based on the Generalized approach for accelerated maximum likelihood based image restoration applied to three-dimensional fluorescence microscopy, but modified to allow for joint reconstruction and with enhancements as described in the technical note. It offers increased robustness to noise and mismatch between the theoretical and real PSF.

Also, it offers more options (likelihood poisson and gaussian, and regularization), allowing choosing an algorithm optimized for specific image types, e.g. sparse and dense images.

Enable Channel Selection

Not possible in combination with Maximum Iterations and Quality Threshold.

Activated: Applies the settings on a channel specific basis. This allows you to set parameters for each channel individually. A separate, colored tab for each of the channels is displayed.

Deactivated: Applies the same settings to all channels of a multichannel image.

2x Upsampling

Activated: Allows you to extract additional information enabled by the SIM principle. This modality splits one pixel into four (2 vertical and 2 horizontal pixels), which allows the algorithm to work on a finer grid for deconvolution and reconstruct with higher resolution. A finer PSF is taken and processed in the same way as 1x resolution. Note that this will largely increase the computation times and requires a large CUDA-based GPU.

Normalization

Specifies how the data of the resulting image is handled if the gray/color levels exceed or fall short of the value range.

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Clip

Clips the values that exceed or fall short of the value range. Sets negative values to 0 (black). If the values exceed the maximum possible gray value of 65636 when the calculation is performed, they are limited to 65636 (pixel is 100% white).

Results from different input images can be quantitatively compared with each other.

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Automatic

Normalizes the output image automatically. In this case the lowest value is 0 and the highest value is the maximum possible gray value in the image (gray value of 65636). The maximum available gray value range is always utilized fully in the resulting image.

Results from different input images cannot directly be compared quantitatively with each other.

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Factor

Only visible if Clip is selected.
Defines a scaling factor for normalization. A factor of 1 or above preserves the original dynamic range information, but high values may be clipped, so the intensity information can be incorrect. A factor below 1 compresses the original dynamic range information, but reduces the clipping effect to keep the pixel intensity relations correct also for bright areas.

Set Strength Manually

Only available for Constrained Iterative and if for Regularization is at least Zero Order selected.

Activated: Sets the desired degree of restoration with the slider. To achieve strong restoration and best contrast, move the slider towards Strong. To achieve lower restoration but smoother results, move the slider towards Weak. If the setting is too strong, image noise may be intensified and other artifacts, such as "ringing", may appear.

Deactivated: Determines the restoration strength for optimum image quality automatically. This is recommended for widefield images and is therefore deactivated by default.

The restoration strength is inversely proportional to the strength of so-called regularization. This is determined automatically with the help of Generalized Cross Validation (GCV).

Convergence History

Visible for Fast Iterative or Constrained Iterative algorithms.

Displays the progress of the calculation as line graph. Several quality parameters are measured for each iteration and once either an optimum or the maximum allowed number of iterations is reached, the processing is stopped. This display allows you to observe directly how the iterative method affects the available data. It also shows how many iterations have been used and how much time is being used per iterations.

Corrections

To display parameters for image correction, click .

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Background

Activated: Analyzes the background component in the image and removes it before the deconvolution calculation. This can prevent background noise being intensified during deconvolution.

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Bad Pixel Correction

Activated: Employs a fully automatic detection and removal of spurious or hot pixels (also known as stuck pixels) in an image stack which might interfere with the deconvolution result.
It is based on the analysis of the gray level variance in the neighborhood of each pixel in the image. It is recommended to use this parameter only, if stuck pixels are observed in the input image.

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Fluorescent Decay

Activated: Corrects bleaching of the sample during acquisition of the z-stack.
This function should only be activated for widefield images. Use it if your sample undergoes strong bleaching during acquisition.

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SIM Correction

Activated: Removes stripe artefacts created by image acquisition and corrects for false phases in metadata.

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Stronger Sectioning

Activated: Applies a stronger optical sectioning to remove out-of-focus signals based on the multiplication of the optical sectioning data.