• Macro editor and recorder.
• User interactions: getNumber, getString and Dialog boxes
• User interruption: waitForUser
• Variables
• User-defined functions, passing arguments
• Calling a plugin from a macro
• Loops and conditional execution
• File browsing and batch processing
• Some simple example macros

FISH (Fluorescent In-Situ Hybridization) is a complex gene staining technique with numerous variants. The quality of the staining depends on related physical parameters such as the level of DNA de-condensation. We will essentially consider here that our protocol allows to label some chromosomes of interest inside human spermatozoids so that
they appear as "bright fluorescent spots". The students will write an ImageJ macro processing images from such FISH assay to segment the spermatozoid nuclei and classify them based on their chromosomal content (multi-
plicity of FISH spots in 3 different fluorescent channels). The workflow will also include some results visualization for simple assessment of the classification quality and statistics computation.

The nuclei of the spermatozoids are DAPI stained and the chromosomes of interest (here X, Y and 18) are FISH stained. The fixed sample is scanned by a motorized stage microscope (widefield or confocal), all the fields of
view necessary to tile the sample are acquired.

            Statistical Analysis of Microtubule Orientation

    Task

    Input Data

In this module the students will be instructed how to track cell movements within the mono-layer sheet of the epithelium of a Drosophila embryo. The segmentation of the cells is performed by an ImageJ macro on the maxi-
mum intensity projection of the original movie, the macro outputs a stack of segmentation masks (one mask per time frame). The tracking is performed in Matlab by importing the segmentation masks. The students will also learn how to identify the junctions (cell-cell adhesions) and the vertices (intersections of junctions), and to visualize the results of the tracking.

The cell membrane expresses a GFP-E-cadherin construct, the tissue of the embryo is imaged in its apical part by a spinning disk microscope. The datasets are provided as the maximum intensity projection of three time-lapses show-
ing different tissue morphologies and dynamics.

Cell migration is driven by polarized dynamics of the actin cytoskeleton and connected focal adhesion sites. In the following project, we learn how to classify detected image objects (focal adhesions) due to different object features (amongst others: actin flow above focal adhesions) by data mining techniques.

1. 6 min time-lapse series of a migrating cell in low temporal resolution. Focal adhesion are imaged in epifluorescence
2. 70s time-lapse series of the same migrating cell in high temporal resolution, imaged immediately after movie 1. Actin is imaged in TIRF.

For this project mice developing some specific tumors are injected a rhodamine-lectin construct to stain their blood vessels before sacrificing. Extracting the local statistics of the blood vessel network inside specific sub-regions of the tumors is a powerful investigation tool: the density of the vascularization and vessel branching points and the thickness of the vessels are all crucial age indicators to understand how the structure developed and possibly necrosed. With the help of a simple ImageJ macro these statistics can be extracted and the network 3D rendered with judicious color/transparency to provide insights on its organization.

The datasets were acquired by a custom macroSPIM (Single Plane Illumination Microscope) allowing to image large (up to 1 cm), fixed and optically cleared samples (pieces of organs, tumors, whole organisms...). 3D stacks of different sub-regions of a subcutaneous tumor (lectin stained blood vessels) are acquired.