Bioimage informatics

This workflow is used to track multiple (appear/disappear, dividing and merging) objects in presumably big 2D+t or 3D+t datasets. It is best suitable for roundish objects or spots. Tracking is done through segmentation, which can be obtained from ilastik pixel classification, or imported from other tools. Users should provide a few object level labels, and the software predicts results on the rest of the image or new images with similar image characteristics. As a result, all objects get assigned random IDs at the first frame of the image sequence and all descendants in the same track (also children objects such as daughter cells) inherit this ID.

The Artemia Tools help to calculate the normalized redness of Artemia in color images.

See: http://dev.mri.cnrs.fr/projects/imagej-macros/wiki/Artemia_Tools

Test images: http://biii.eu/node/1139

This tool allows for extraction of image series from Olympus Slide Scanners. These VSI files usually contain several images that are too big to load into memory (>50k x 50k pixels). It was written and tested on Fiji and is available from a Fiji Update Site: http://fiji.sc/List_of_update_sites

In this human cytoplasm-nucleus translocation assay, learn how to load a previously calculated illumination correction function for two separate channels, measure protein content in the nucleus and cytoplasm, and calculate the ratio as a measure of translocation. This is a clumpy cell type, so studying the settings in primary object identification may be helpful for users interested in the more advanced options that module offers. More about these images can be found at the BBBC.

If your images are corrupted by a strong dominant Gaussian noise you can try this simple filter. It is based on thresholding in the DCT domain and is usually vastly superior to typical Gaussian filtering in term of detail preservation / noise reduction trade-off. The filter unfortunately introduces some block like artifacts that can be mitigated by averaging out overlaping shifted windows (as implemented in the Matlab version) and performing maximum intensity projection after the filtering: As such the filter is way more adapted to process 3D stacks that you plan to maximum intensity project than to process single z slice images.