Nis element imaging software
NIS-Element imaging software is Nikon's comprehensive and advanced imaging platform. It provides a suite of tools for capturing, analyzing, and managing digital images acquired from Nikon microscopes and cameras. The software enables users to perform a variety of imaging tasks, including image acquisition, processing, measurement, and annotation.
Lab products found in correlation
26 protocols using nis element imaging software
Stomatal Trait Analysis Protocol
Stomatal Imaging and Quantification
Immunocytochemical Analysis of PD-L2 Expression
Quantitative Microscopy of Fluorescently-Tagged Proteins
Immunohistochemical Analysis of Xenograft Tumors
Calcein-AM Cell Imaging Protocol
Organelle Localization in MKN45 Cells
Immunofluorescent Identification of CTCs
Histological analysis of tumor samples
Particle Tracking in Microfluidics
in microtiter wells were made on a Nikon Ti confocal microscope (Nikon
Instruments Europe BV, The Netherlands) at a magnification of 20×
using an iXon Ultra 897 EMCCD camera (Andor, Belfast, UK) in bright-field
illumination conditions, using Nikon NIS-Element imaging software.
The positions of the particles were recorded in a field of view of
410 × 410 μm2 at a frame rate of 33 Hz with
an exposure time of 5 ms. The particles were localized using phasor-based
localization, after which the x–y trajectories were used to calculate the mean squared displacement
over time using a sliding window algorithm. To discriminate between
unbound and bound states of particles, a threshold on the calculated
diffusion coefficient was set at 0.12 μm2/s.
Tracking of tethered particles in flow chambers was done on a custom-made
optical setup at a total magnification of 10× using a Grasshopper
camera (Point Grey Research Grasshopper3 GS3-U3-23S6M, 1920 ×
1200, pixel format: 8 raw, gain 10) in bright field illumination conditions.
The positions of the particles were recorded in a field of view of
659 × 493 μm2 at a frame rate of 30 Hz with
an exposure time of 5 ms. The particles were localized using phasor-based
localization, after which the x–y trajectories were used to detect particle switching events using
a change-point detection algorithm, which has been described by Bergkamp
et al.14 (link)
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