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Comprehensive Imaging Software
NIS-Elements Imaging Software allows integrated control of microscopes and peripheral devices, as well as confocal systems. In addition to various functions for confocal imaging, it has a wide range of AI tools that support streamlining of image analysis and optional modules that enable customization of analysis and experiment workflows.
NIS-Elements ER can be used to improve confocal spatial resolution up to 120 nm (lateral)/300nm (axial) using GPU-processing with automatic parameter settings and user-defined options.
Customized Definition of Experiments
NIS-Elements has built-in multidimensional (multi-XY,Z,T, multichannel) experiment capabilities. Adding the optional JOBS module allows even more customization such as setting up non-orthogonal experiments with multiple paths and dimensions. Oftentimes, experiments require customization to streamline acquisition and capture all necessary data points. Analysis of data can be done even in real-time during the experiment, and the direction of the experiment can even be changed based on the results of the analysis. Users have ultimate flexibility in designing experiments that maximize their data output needs.
JOBS Experiment Protocol
From acquisition to analysis, Nikon’s NIS-Elements software is a pioneering leader in the implementation of convolutional neural network (CNN) based deep learning for microscopy. Several AI tools are available, many targeted specifically for assisting users in acquiring, processing, and analyzing confocal data. These tools aid users in achieving adequate signal-to-noise ratio (SNR) images for image processing and analysis, and more tools for both segmentation and image enhancement or modality transformation.
Confocal imaging has multiple variables that must be fine-tuned for the best image quality, a statistically valid signal-to-noise ratio, and long-term sample stability. NIS-Elements AI tools are designed to assist in achieving these targets.
New for AX/AX R: Autosignal.ai can suggest the best illumination and detection settings automatically, instead of users manually attempting to find the best settings by trial and error, or while scanning live and exposing the sample unnecessarily.
Shot noise is the main noise source in confocal imaging. Denoise.ai can remove the shot noise component from confocal images, improving the image quality and assisting in downstream segmentation.
A toolbox of AI functions assist users in easy segmentation of images; after training the AI, segmentation that would take hours by traditional methods (such as samples with uniform intensity, making traditional thresholding of different morphologies nearly impossible) can be done in seconds.