Affordable, Clear Images In A Fraction Of The Time
As the preferred deconvolution standard, AutoQuant X3, is the most complete deconvolution software 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.
Now, the easiest to use, most reliable deconvolution software package on the market just got better. Introducing Graphics Processing Unit driven Deconvolution for AutoQuant X3. Adding the module to the current AutoQuant X3 platform maintains the current ease of use, while adding the speed of GPU processing to your current platform.
Click below to learn more about the AutoQuant X3 GPU Module
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 software 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 ConnectorImport and export images and data to any supported package with ease.
ROI PreviewThe ROI preview provides customers the opportunity to test the settings prior to processing.
Easy to use interfaceAutoquant X is engineered with a high resolution, user friendly interface.
Blind DeconvolutionDeconvolve images with the most powerful Maximum Likelihood Estimation (MLE) available.
GPU ProcessingEasily add a GPU module to your AutoQuant X3.1 software platform to decrease processing time and increase your throughput.
Batch ProcessingQuickly load multiple image sets to be automatically aligned and deconvolved sequentially while optimizing the system resources for faster processing.
Optimize your time
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.