Public data sets
Do you need image data to try your algorithms on? Do you lack expert ground truth to test your methods? No problem! Here you have a list of available public data sets from the Fiji community and other sources:
- Segmented ssTEM stack of neural tissue, thanks to Albert Cardona.
- 30 sections from a serial section Transmission Electron Microscopy (ssTEM) data set of the Drosophila first instar larva ventral nerve cord (VNC). The microcube measures 2 x 2 x 1.5 microns approx., with a resolution of 4x4x50 nm/pixel.
- The challenge: use this data set to train machine learning software for the purpose of automatic segmentation of neural structures in ssTEM.
- The images are representative of actual images in the real-world: there is a bit of noise; there are image registration errors; there is even a small stitching error in one section. None of these led to any difficulties in the manual labeling of each element in the image stack by an expert human neuroanatomist. A software application that aims at removing or reducing human operation must be able to cope with all these issues.
- Sample data at LOCI, in a variety of file formats.
- Sample OME-TIFF data on ome-xml.org, thanks to Josh Bembenek.
- The dataset consists of tubulin histone GFP coexpressing C. elegans embryos. All image planes were collected at 512x512 resolution in 8-bit grayscale.
- Migrating macrophages in response to stimuli.