• AQX3 heroshot2
    AutoQuant X3


    As the preferred deconvolution standard, Autoquant X3, is the most complete package of 2D and 3D restoration algorithms available.

    AutoQuant X3 makes it simple to deconvolve image sets and visualize them in time, Z, and channel, and analyze all parameters within the same, easy to use application.


    Why Deconvolve?

    Image Restoration

    Restoring Fidelity

    Restoring Fidelity

    The Deconvolution process restores the fidelity and enhances the quality of images which have undergone inherent, and often inevitable, distortions during the image acquisition process. The inherent optical limitations of microscopes, combined with sample characteristics and imaging techniques, often introduce blurring and other types of noise, which compromise image quality.

    AutoQuant's deconvolution tools greatly improve both the image resolution and its contrast, leading to enhanced visualization, better measurements, and more meaningful analysis.

    Set Up Easily

    • Work Flow Connector
    • ROI Preview
    • easy to use interface2
    • Work Flow Connector

      Import and export images and data to any supported package with ease.
    • ROI Preview

      The ROI preview provides customers the opportunity to test the settings prior to processing.
    • Easy to use interface

      Autoquant X is engineered with a high resolution, user friendly interface.

    Apply Easily

    • autoquant blind decon2
    • autoquant custom gibson lanni modeling
    • autoquant batch processing2
    • Blind Deconvolution

      Deconvolve images with the most powerful Maximum Likelihood Estimation (MLE) available.
    • Custom Gibson-Lanni Modeling

      Establish Point Spread Function (PSF) modeling algorithm for Theoretical PSF determination as well as Spherical Aberration (SA) detection and correction.
    • Batch Processing

      Quickly load multiple image sets to be automatically aligned and deconvolved sequentially while optimizing the system resources for faster processing.
    Faster Deconvolution Times
    Combine batch processing with our optimized algorithms to process images faster than ever before.


    Save your individual settings
    Optimize your time by saving your customizable configuration settings for software and hardware preferences.


    Objective, Camera, and Dye Lists
    The imaging markets most complete list of supported hardware compo-nents and Dye spectral information.


    Simplify your choices
    One product that provides all your needs. Easily select the optimal Algorithm that fits your requirements without trying to filter through complex packages and a myriad of material numbers.



    Understanding How it all Works

    A "first guess" at the unblurred object is made, typically either by processing the observed image through an inverse filter, or by simply using the Observed Image itself. This becomes the initial Object Estimate.

    Mouse over the below objects to reveal further details.

    Decon Flowchart

    The Object Estimate is convolved with the PSF to produce an Image Estimate.

    The Image Estimate is compared with the Observed Image to produce an Error estimate.

    The new Object Estimate (and, if applicable, the new PSF Estimate) are fed back to Object Estimate, and the process continues until a set number of iterations has been performed.

    The Error estimate is then used to produce a new Object Estimate, subject to constraints (such as non-negativity) that prevent the estimate from diverging away from a reasonable solution. In a blind deconvolution, the Error estimate is also used to produce a new PSF Estimate, subject to a more stringent set of constraints that prevent it from deviating unreasonably from its original form.


    Batch Deconvolution

    Optimize your time

    Queue your image sets
    Select your images or image stacks and Algorithm, even, add auto alignment.
    Que your image sets
    Deconvolve Automatically
    Deconvolve your images at an offline workstation or set a start time when the system is not being utilized.
    Deconvolve Automatically
    Use one or more of the many built in measurement tools to compare results to the original or other deconvolved images.


    Proven Powerful Algorithms

    Select your Optimal Algorithm

    • Use for a quick “preview” of a deblurred version of your data

      No/Nearest Neighbor

    • Constrained iterative deconvolution for single-plane images (including multi-channel and multi-timepoint). Not as quick as a simple filter like No/Nearest Neighbors, but provides the best results for 2D images, and offers an option to perform processing without any knowledge of optical parameters.

      2D Blind Deconvolution

    • Inverse Filter
    • Constrained iterative deconvolution for multi-plane image stacks (including multi-channel and multi-timepoint). Not as quick as a simple filter like Inverse Filter, but provides the best results for 3D images when a good measured PSF is not available.

      Non-Blind Deconvolution

    • Constrained iterative deconvolution for multi-plane image stacks (including multi-channel and multi-timepoint). Not as quick as a simple filter like Inverse Filter, but provides the best results for 3D images when the initial PSF is believed to be accurate (such as when it has been collected in tandem with the sample, or should be quite close to the theoretical model).

      Non-Blind Deconvolution

    • No/Nearest Neighbor

      Simple and quick subtraction of blur.
    • 2D Blind Deconvolution

      Quantitative iterative deconvolution, optimized for 2D images.
    • Inverse Filter

      Simple, non-iterative blur reversal based on a calculated PSF.
    • Adaptive Blind

      Quantitative iterative deconvolution for 3D stacks that can adapt a PSF to the data.
    • Non-Blind Deconvolution

      Quantitative iterative deconvolution for 3D stacks, best used with a measured PSF.
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