Component

A Component is an implementation of certain image processing / analysis algorithms.

Each component alone does not solve a Bioimage Analysis problem.

These problems can be addressed by combining such components into workflows.

Description

A clear tutorial on how to write a MATLAB script to segment clustered cells.

The full script is downloadable near the bottom of the article. 

Description

Matlab toolbox to analyze single molecule mRNA FISH data. Allows counting the number of mature and nascent transcripts in 3D images. See 2513. Following toolboxes are required: - Optimization toolbox - Statistics toolbox - Image processing toolbox - (Optional) Parallel processing toolbox

 

Input data type: 3D image

Output data type: CSV

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Description

A Jython script using the plugin : Register Virtual Stack Slices It takes a sequence of image slices stored in a folder, and delivers a list of registered image slices (with enlarged canvas). One of the images in the sequence can be selected by the user as reference and it will remain intact. The plugin can perform 6 types of image registration techniques: - Translation - Rigid (translation + rotation) - Similarity (translation + rotation + isotropic scaling) - Affine - Elastic (via bUnwarpJ with cubic B-splines) - Moving least squares All models are aided by automatically extracted SIFT features.

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Description

(from the webpage) >This usage example shows how to produce two-color images from spectrally unmixed data sets. It was written for an Alexa647/Alexa700 measurement on the Würzburg 1 biplane setup as documented in [Aufmkolk2012]. The first two tasks in this example produce prerequisite knowledge for the image generation, the alignment information (Produce linear alignment matrix) and the F2 ratios, i.e. the relative intensity of fluorophores between the channels. [Aufmkolk2012] Hochauflösende Mehrfarben-Fluoeszenzmikroskopie. Sarah Aufmkolk. Julius-Maximilians-Universität Würzburg. 2012-mar.

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Description

The ImageJ pligin, called PixFRET, allows a simple and rapid determination of channel bleed-through parameters and the display of normalized FRET images. see 2521

 

Input data type: 

Stacks with 2 channels (controls for bleed-through calculation) or 3 channels (FRET calculation)

Output data type: 

One Image with FRET values and One image with normalized FRET values