Software Resources

NIS-Elements Viewer

NIS-Elements Viewer is a free standalone program to view image files and datasets. It offers the same powerful view and image selection modes as the NIS-Elements core packages: Volume View with 3D Rendering, Tile View for Time, Z and Multipoint datasets, and Slice View for Z and Time datasets. The NIS-Elements Viewer also has the same look and feel as the NIS-Elements core packages. For example, calibrations, and binary layers (thresholded objects) created in the core package also port over to the NIS-Elements Viewer. In addition, image header information and experimental information such as time interval, Z step and device parameters are accessible (Windows version only). Saving ND datasets to TIFF files is also built into the NIS-Elements Viewer.

Download NIS-Elements Viewer User’s Guide (738 KB)

Windows Viewer

Minimum System Requirements

  • CPU Core 2 Duo or higher
  • Windows 10 Pro or later
  • 64 bit only
  • Direct X version 11 or higher

Download

Mac OS X Viewer

Minimum System Requirements

  • CPU Core 2 Duo or higher
  • OS Mac OS X 10.6 or later
  • Video NVIDIA or ATI Radeon Graphics Card Recommended

Download

Denoise.ai – Trained Artificial Intelligence algorithm for confocal image denoising

Using a convolutional neural network using an MXNET framework encoded with several thousand examples of resonant confocal data, the input image data is assigned learnable weights, which results in teaching of the network to make correlations and recognize patterns: with the main common pattern being Poisson shot noise, the network was trained to recognize and remove shot noise from resonant A1 confocal data sets. This trained Artificial Intelligence (AI) algorithm can then be used even in real-time for noise removal.

With Denoise.AI
Original

Maximum intensity projection resonant confocal image of multi-labeled Danio sp. prepared by Callen Wallace and Mike Calderon, Center for Biological Imaging, University of Pittsburgh for the Quantitative Fluorescence Microscopy (QFM) Course.


Advanced 2D and 3D deconvolution algorithms for enhanced image quality

NIS-Elements offers advanced 3D and 2D deconvolution modules for improving image quality. Upload your image to our NIS-Elements deconvolution test site to see the difference.

Visit Website

Deconvolved
Original