Mobile Version
Under Construction

Please view on Desktop for the best experience

Contact: +65 6245 4965

Email: support@asiaimaging.com

 
 
 
 

AutoQuant Deconvolution

Clearer 2D and 3D images in a fraction of the time

Before & After Gallery

Connect every aspect of your imaging
workflow using a single solution

Convolution + Noise = a 'Blurry' image

AutoQuant Deconvolution greatly improves both the image resolution and contrast, leading to enhanced visualization, better measurements, and more meaningful analysis. To do this, both the convolution and noise are handled to take your images from blurry to beautiful.

When light waves encounter an object – such as the sample of interest, a lens, or even air molecules – they scatter & bend. Within an optical system, such as a microscope, this effect on a light wave is called the point-spread function, commonly abbreviated to PSF.
The PSF applies to every point of light passing through the optical system, in a process called convolution.

Digital images invariably suffer from the addition of some amount of noise that is introduced through a combination of ambient factors and the materials and electronics present in the digital camera hardware.
Signal-dependent noise can be characterized by a Poisson distribution, while noise arising from the imaging system often follows a Gaussian distribution.

Intuitive Guided Process

AutoQuant is still the most intuitive deconvolution software in the industry, using a simple yet elegant workflow to direct any user through the necessary steps to achieve repeatable image restoration.

01

Confirm Image Metadata

02

Confirm Channel Metadata

03

Choose Starting PSF

04

Choose Deconvolution Settings

05

Deconvolve!

Straightforward Point-Spread Function (PSF) Models for Common Microscopy Modalities

Measure the PSF experimentally by collecting an image of a sub-resolution bead. When this small, the bead image
represents the PSF of the microscope and appears as a single point of light that has been blurred.

Advantages
  • Provides a very accurate representation of the PSF
  • Includes & corrects for aberrations in the imaging system
  • Can be used with modalities unavailable as Theoretical
Disadvantages
  • Difficult and time consuming to collect correctly
  • Can potentially misrepresent the PSF if collected improperly
  • Widefield EPI Fluorescence
  • STEDNew
  • Spinning Disk Confocal
  • Two Photon (Multi-Photon)
  • Confocal EPI Fluorescence
  • Other

Save time and effort collecting a measured PSF by using optical parameters such as Microscope modality, X, Y, & Z spacing, Objective Lens Numerical Aperture, and Refractive index of the medium to generate an accurate Theoretical model.

Advantages
  • Saves time over collecting accurate bead images
  • Not subject to changing variations in collection conditions
Disadvantages
  • Limited to the modalities supported by the software
  • Less accurate than a properly collected bead image
  • Widefield EPI Fluorescence
  • STEDNew
  • Spinning Disk Confocal
  • Two Photon (Multi-Photon)
  • Confocal EPI Fluorescence
  • Other

Generates an initial PSF estimate from an auto-correction of the image data. This method requires only the image itself as an input.

Advantages
  • Doesn't require bead images or optical parameters
  • Allows just about any modality to be deconvolved
Disadvantages
  • Available only for single plane (2D) images/sets
  • Requires more iterations and is susceptible to over-processing
  • Widefield EPI Fluorescence
  • STEDNew
  • Spinning Disk Confocal
  • Two Photon (Multi-Photon)
  • Confocal EPI Fluorescence
  • Other

Time tested and still trustworthy

While integrating the time-tested deconvolution algorithm in the new Image-Pro module, we conducted a series of laboratory tests to ensure the new integration is still trustworthy and that it still delivers reliable, repeatable results, even within a new platform. The whitepaper below details the results and conclusions of those tests.In short, all of our new tests yielded reassuring outcomes. The AutoQuant Fixed PSF and Adaptive PSF algorithms continue to deliver consistent improvement and reliable data in all cases, especially for 3D data where we observed nearly identical improvement. Indeed, none of our tests showed a significant difference in results. Therefore, the new module has been streamlined to focus on the Fixed PSF algorithm alone for 3D images, making setup faster and generating the same quality data as previous AutoQuant versions.

View Whitepaper
Deconvolve Images Faster with Built-in GPU Acceleration

For computationally-intensive applications like deconvolution, being able to process thousands of mathematical calculations at once is preferable to processing a few at a time. In short, you have more bandwidth available when you utilize the GPU rather than the CPU allowing for faster processing of the image.

Image Size

Deconvolution Time

GPU Accelerated

GPU Accelerated

The CPU-GPU Collaboration

Certain portions of the deconvolution process still occur on the CPU, notably the initial setup. Once this is complete, AutoQuant accesses the many GPU processor cores that carry out the actual iterative deconvolution. The final results are then transferred back to the CPU and saved.

Step 1: Initial Setup

Allocate memory and initialize math libraries

Step 2:Transfer Data to GPU

Step 3: Perform Iterations

Convolve image guess with PSF guess. Compare the results with the original data. Update the image and (if bling) PSF guess. Continue to the next iteration.

Step 4: Retrieve Result from GPU

Multiple Cores

The core count on a high-end workstation’s CPU(s) will typically be around 32. In contrast, the core counts reported on even consumer-grade GPUs number into the thousands.

Thousands of Cores

The individual processor cores on a GPU are considerably slower than most CPU processor cores, but what they lack in power, they more than make up for in numbers.

Batch Processing

Use Image-Pro's native Batch Processing to select a folder of similar images to be deconvolved.

  • Save valuable time. Set up the batch and walk away.
  • Deconvolve groups of images from the same experiment without the need to write custom macros.
  • Choose either a fixed or adaptive PSF and apply it to the whole batch.
  • Automatically save deconvolved datasets for review and analysis.

AutoQuant

AutoQuant

Use it alone or combine it with Image-Pro modules for an even more powerful solution.

3D Viewer

2D Automated Analysis

3D Analysis

How does the new Module stack up against the older Standalone software?

Standalone New Module
Macro language
OME file and metadata support
Theoretical PSF for STED Modality
3D Movie Maker
3D Viewer
Image Adjustments and Correction
Image Import and Set Builder
Spherical Aberration Correction
Batch Processing
GPU Acceleration
Inverse Filter
No/Nearest Neighbors Algorithm
DIC Restoration