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NIS-Elements Advanced Research

eagle-i ID

http://meharry.eagle-i.net/i/00000136-eb58-8481-e4ae-260d80000000

Resource Type

  1. Software

Properties

  1. Resource Description
    NIS-Elements performs live cell, 6D experiments quickly and flawlessly. It can organize X, Y, Z, Lambda (wavelength) and Time within one integral platform, for easier-than-ever multi-dimensional imaging. Four types of “dimensions” of acquisition – Time, Multipoint, Z-series, Wavelength (Multichannel)— can be selected. NIS-Elements innovative analysis capabilities include object counting, automated measurements, region of intent measurements and time measurements including image ratioing of multi-channel images. Advanced visualization methods, like capturing 3D data sets, 2D/3D data set analysis, and large image stitching can all be performed with relative ease with the software. NIS-Elements offers a rich spectrum of mathematical morphology functions (clean, erode, dilate, open, close, smooth), morphologic separation functions, linear morphology functions, fill functions (fill holes, close holes), skeleton functions (medial axis, skeletonize, pruning) and other functions (such as: binary invert, convex hull, contour, skeletonize, homotopic marking, zones of influence, etc.) Multiple single channel images (captured with different optical filters or under different camera settings) can be merged together simply by dragging from one image to another. In addition, the combined images can be stored to a file while maintaining their original bit depths or optionally can be converted into a RGB image.
  2. Manufacturer
    Nikon Corporation
  3. Used by
    Morphology Core
  4. Website(s)
    http://www.nis-elements.com/ar.html
 
RDFRDF
 
Provenance Metadata About This Resource Record
  1. workflow state
    Published
  2. contributor
    sgarner
  3. created
    2012-04-25T16:13:42.519-05:00
  4. creator
    TPatel
  5. modified
    2012-09-20T08:58:48.793-05:00

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016