Manual

Microtubule end tracking in live cell fluorescent images of Drosophila oocyte involves overcoming the following challenges, which can be tackled by a series of preprocessing steps and tracking described in Parton et al (2011)

• illumination flicker & photobleaching: suppress by normalising intensities, e.g. using Image->Adjust->Bleach Correction in Fiji/ImageJ
• uneven illumination: Fourier bandpass filtering (e.g. Process->FFT->Bandpass Filter) preserves features within a selected size range
• high background / poor contrast: foreground filter, e.g. Temporal Median filter
• tracking: e.g. TrackMate in Fiji/ImageJ (segmentation using DoG detector)

Simple workflow description for ImageJ, step-by-step description for delineating focal adhesions, count and characterize their positions.  

Measurement of dynamics is not involved.

An ActionBar is a simple annotated text document that has snippets of Imagej macros or Beanshell arranged into buttons. This tool is very useful when creating custom work flows integrating multiple components. Each component can be linked to a button for a more streamlined and accessible workflow.

It explains how to use ImageJ to compare the density (aka intensity) of bands on an agar gel or western blot.

Some notes can be found here: http://cellnetmcweb.bioquant.uni-heidelberg.de/image-analysis/ShortTutorials/Fiji_GelAnalyzer.pdf

ITK-SNAP is a software application used to segment structures in 3D medical images. It can also be used as a 3D annotation tool for deep learning. It is based on ITK, VTK libraries.