Tutorial

This module follow EB1 tracking with IJ. In this session, we will visualize the tracking results and also cover typical analysis protocols for the quantitative analysis of movement. Two dynamic numerical features could be extracted from tracking results: speed and direction. Estimation of movement speed from multiple trajectories is a popular indicator of movement, and we will quickly go over the method for estimating the average speed of EB1 movement along microtubule. Movement direction is another quantitative feature, but is rarely explored.

We take an example image data of microtubule binding protein EB1, and will study how to automatically track those signals and how to analyze the tracking results. We use ImageJ for measuring the temporal changes in signal positions, and will feed the tracking results for analyzing their dynamics using Matlab in the following session EB1 tracking with Matlab.

We will cover the theory behind some useful image preprocessing operations such as filtering for image restoration and feature enhancements, illumination compensation and background correction. We will then combine these operations and write a complete image analysis macro including image correction and 2D stitching of images coming from a large multiposition experiment.