AutoQuant X: Deconvolution & 3D Visualization Imaging Software

AutoQuant X V.2.2.0

AutoQuant X deconvoultion software produces images with increased resolution, better contrast and improved signal-to-noise ratio and is becoming a standard part of digital microscopy, especially in the life sciences.

 

OVERVIEW


Widefield Images

 

Raw

Deconvolution

Raw versus Deconvolution

 

Raw versus Deconvolution

 

Raw versus Deconvolution

 

Raw versus Deconvolution

 


Downloads:


AutoDeblur & AutoVisualize Brochure AutoDeblur & AutoVisualize Brochure
Clearing Up Deconvolution Brochure Clearing Up Deconvolution Brochure

 

AutoQuant X consists of two of the most advanced image deconvolution and 3D visualization software products available today! AutoQuant X comes with both AutoDeblur and AutoVisualize.

AutoDeblur

Offers the most powerful Deconvolution tools, including AutoQuant X's proprietary Blind Deconvolution. The Blind Deconvolution algorithm is both iterative and constrained, yet unlike other deconvolution products, it does not require the manual calibration and measurement of the point spread function (PSF). Instead, it constructs the PSF directly from the collected data set.

All microscopes are limited by the laws of physics, and these laws state that when light passes through a medium, that light will bend. This is one of the most common causes of haze and blur in microscopy images. Deconvolution can correct this problem, not only removing the haze and blur, but restoring vital detail to datasets.

AutoDeblur works with Widefield Epi-Fluorescence, DIC, Transmitted-Light Brightfield and most Confocal microscopes including Two-Photon and Spinning Disk.

On the hardware side of the application, AutoDeblur is also multithreaded. This gives you the ability to run concurrent processes. To take it a step further, dual processors can be utilized to their maximum potential by running CPU intensive processes concurrently on each one (such as deconvolution).

Please note, AutoQuant X operates most efficiently with a 64-bit Windows computer. While a 32-bit Windows machine can be used, processing time will increase ten fold.


Deconvolution Pollen Grains

 

AutoVisualize

 


Downloads:


AutoDeblur & AutoVisualize Brochure AutoDeblur & AutoVisualize Brochure
Clearing Up Deconvolution Brochure Clearing Up Deconvolution Brochure

 

AutoVisualize

The goal of creating, enhancing, and saving images is to see, analyze and measure them, from all angles. AutoVisualizewill let you do just that. With AutoQuant X's 5D Viewer, time-series datasets can be rotated through time to any angle, an orthogonal slice can be moved through the dataset, you can create movies showing the full rotation of the dataset, multiple projections are available for dynamic display of your dataset.

Side by side before and after comparison has never been easier than now with AutoQuant X’s multiPreviewer capability. Multiple concurrent 5D Viewers can be opened and synchronized for striking comparisons of data. Use the Movie Maker feature to create an .avi file of a movie as your data rotates through time, and use it in a PowerPoint presentation, or post it to the web.

Additionally, deconvolving and viewing the dataset are only part of the process; once these are done, analysis is the next step. With AutoVisualize, you can measure distances between objects, measure the surface area and volume of objects, and calculate statistics on the dataset.


Colocalization

Colocalization

Colocalization

Image-Pro Express is the cost-effective image enhancement software perfect for basic imaging or image capture stations.

As the first step in the Image-Pro software series, Image-Pro Express comes equipped with the basic features needed to capture and enhance images for scientific, medical, and industrial research.


FRET

FRET

FRET

Created for researchers focusing on protein-protein interactions, our FRET module incorporates the two most commonly accepted algorithms: Elangovan and Periasamy, and Gordon and Herman, and adds our own proprietary algorithm as well. All three algorithms correct Cross Talk, but AutoQuant X's proprietary algorithm goes one step further. Where other algorithms make assumptions about the Cross Talk, our Maximum Likelihood Estimation algorithm mathematically solves the Cross Talk, allowing for a much more accurate analysis of the images.

FRET X also includes several helpful preprocessing tools to turn your images into precisely analyzed statistics. The Channel to Channel alignment tool corrects for shifts between channels, shifts that would otherwise corrupt your analyses. The Background Subtraction tool eliminates artifacts that can compromise the results of your analyses.


Image Alignment

Image Alignment

A common problem during 3D image acquisition is misalignment between the slices due to stage vibration, filter cube, or a host of any other causes. AutoQuant X's Image Alignment module is the cure for this ill. With powerful and accurate algorithms for slice to slice alignment as well as channel to channel alignment, AutoQuant X can correct virtually any misalignment issue. Our Image Alignment feature handles problems from vertical to horizontal shift, warping, as well as rotation.


Object Counting and Tracking

Object Counting and Tracking

Object Counting and Tracking

Object Counting and Tracking

The ultimate in time-series image analysis, our Object Counting and Tracking module has the ability to count a nearly infinite number of objects. Our platform is multiDimensional compatible, and can load and process 3D time-series datasets, making it the ultimate tool for counting and tracking 3D objects through time. Counting and Tracking X has powerful and intuitive preprocessing tools to give complete control over the objects to be counted and tracked.

Once the objects have been counted, the objects can then be tracked through the time series. Easy to follow tracking lines show where the object has moved through time, for a vivid graphic depiction of the objects’ activities.

Finally, properties such as the size, circularity, volume, speed, acceleration, distance traveled between time-points and much more can be calculated and exported to a spreadsheet for later analysis.


Ratiometrics

Ratiometrics

Ratiometrics

This module is tailored for intercellular ionic imaging. Designed for researchers who study the effect of changing the environment of a sample by comparing the same sample with differing concentrations of calcium, or changing the pH, Ratiometrics X fills the bill.

Ratiometrics X employs the Grynkiewicz Equation for Ion Concentration and produces accurate results with visually-emphasized color mapping.

Built in pre and postprocessing steps such as Automatic Alignment, Remove Spot Noise and Gaussian Smoothing make for a cleaner resultant image with less steps for the user.

Once the preprocessing has been done, Ratiometrics X delivers concise statistics, and is easily exported into an xls file. Select specific areas to analyze by creating regions of interest, fully defined by the user. Get the results you need from the areas you want.


Deconvolution Algorithms

No/Nearest Neighbor - The No/Nearest Neighbor algorithms work by deblurring one 2D image slice at time. They utilize a subtractive approach based on the simplifying approximation that the out-of-focus contribution in the image slice is equal to a blurred version of the collected adjacent slices. These algorithms are fast, qualitative and work particularly well on images with strong signal to noise ratios.

Inverse Filter - The Inverse filter or Wiener filter is a one-step image process performed in Fourier space by dividing the captured image by the PSF. This algorithm is a fast and effective way to remove the majority of the blur from widefield images using a symmetric or spherically-aberrated theoretical or acquired point spread function. Image noise is managed through an adjustable smoothing operation applied during processing. Algorithm results are qualitative and generally better than the no/nearest neighbor algorithms especially in the XZ and YZ perspectives.

Non-Blind - Non-Blind Deconvolution is a constrained iterative approach that requires a measured or synthetically acquired PSF for processing. This algorithm is based on the same statistical and computational foundation of AutoQuant's renowned Adaptive Blind algorithm and shares the same superior noise handling characteristics and flexibility. However, the PSF provided is assumed to be accurate and is not modified during the deconvolution. Non-Blind offers an excellent balance between quality results, quantitative analysis and time to process.

Adaptive Blind - AutoQuant's Blind Deconvolution algorithm draws upon the statistical techniques of Maximum Likelihood Estimation (MLE) and Constrained Iteration (CI) to produce the most robust and statistically accurate results available on the market today. It does not require a measured or acquired PSF, but instead iteratively reconstructs both the underlying PSF and best image solution possible from the collected 3D dataset. It is well suited for environments where signal to noise ratios are challenging and operates across the full spectrum of modalities.

2D Blind - 2D Blind Deconvolution is an adaptive method for 2D data that does not require your microscope and image parameters. 2D Blind Deconvolution works by iteratively improving the data set and works with time series image sets, individual color channels or intensity images. 2D Blind Deconvolution is capable of restoring features at a sub-pixel resolution level and can work with almost any 2D image.

2D Real-time - Uses AutoQuant's powerful 2D blind deconvolution algorithm to remove blur from a single image. No microscope or image parameters are required. Useful Sharper/Smoother, thickner/thinner and brighter/dimmer controls help guide you to get the very most out of your data. Deblur one frame instantaneously or several in near real-time.

NEWS FEED: