Mac

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. 

A workflow template to analyze subcellular structures in fluorescence 2D/3D microscopy images based on a Fiji plugin **Squassh** is described in Rizek et al (2014).

The workflow employs detecting, segmenting, and quantifying subcellular structures. For segmentation, it accounts for the microscope optics and for uneven image background. Further analyses include both colocalization and shape analyses. However, it does not work directly for time-lapse data. A brief summary note can be found here.

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

The linked webpage presents a collection of ImageJ macros for Intelligent Imaging (Feedback to microscope system for the secondary scan). 

An ImageJ macro able to control some microscopes (Micro-manager or Leica CAM controlled) to acquire high resolution images of only some structures (e.g. isolated cells) or events (e.g. mitosis) within a sample. The scan is sequenced as a primary (low resolution monitoring) scan and a secondary (high resolution, multi-dimensional) scan.

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.