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The script editor in Fiji supports rapid prototyping of scripts and ImageJ plugins, making Fiji a powerful tool to develop new image processing algorithms and explore new image processing techniques with ImageJ. [16] [17]
This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction.
[2] [3] Its first version, ImageJ 1.x, is developed in the public domain, while ImageJ2 and the related projects SciJava, ImgLib2, and SCIFIO are licensed with a permissive BSD-2 license. [4] ImageJ was designed with an open architecture that provides extensibility via Java plugins and recordable macros. [5]
The Colocalization Benchmark Source (CBS) is a free collection of downloadable images to test and validate the degree of colocalization of markers in any fluorescence microscopy studies. Colocalization is a visual phenomenon when two molecules of interest are associated with the same structures in the cells and potentially share common ...
Attempts to rectify this include re-examination and revision of some of the coefficients, [7] [8] application of a factor to correct for noise, [1] "Replicate based noise corrected correlations for accurate measurements of colocalization". [9] and the proposal of further protocols, [10] which were thoroughly reviewed by Bolte and Cordelieres ...
Implementation of Otsu's thresholding method as GIMP-plugin using Script-Fu (a Scheme-based language) Lecture notes on thresholding – covers the Otsu method; A plugin for ImageJ using Otsu's method to do the threshold; A full explanation of Otsu's method with a working example and Java implementation; Implementation of Otsu's method in ITK
Simple interactive object extraction (SIOX) is an algorithm for extracting foreground objects from color images and videos with very little user interaction. [1] It has been implemented as "foreground selection" tool in the GIMP (since version 2.3.3), as part of the tracer tool in Inkscape (since 0.44pre3), and as function in ImageJ and Fiji (plug-in).
Image registration or image alignment algorithms can be classified into intensity-based and feature-based. [3] One of the images is referred to as the moving or source and the others are referred to as the target, fixed or sensed images.