einarolafsson/spacr-example-timelapse-bacteria

spaCR example data: Corynebacterium glutamicum microcolony (phase contrast)

A time-lapse movie with ground-truth instance masks in every frame and the published lineage, for the Time mode and lineage tools of spaCR's Make Masks ("Load test data", "Timelapse: bacteria"). It opens with its masks loaded; the lineage is embedded in the mask TIFFs, so the divisions are on the lineage menu as soon as the sequence opens.

What it shows

A C. glutamicum monolayer microcolony growing in a microfluidic chamber, one frame per minute at 0.072 um per pixel. Rods divide into two daughters throughout the movie and are pushed along as the colony expands.

organism	Corynebacterium glutamicum ATCC 13032
modality	phase contrast
frames	60 (source frames 440-499)
image size	1094x938 pixels
cells per frame	93 to 152 (median 116)
tracked cells	211
divisions	59

Files

• cglutamicum_00_t000.tif ...: one grey image per frame (zlib TIFF).
• ground_truth_masks/cglutamicum_00_t000.tif ...: one uint32 label mask per frame. The pixel value is the source track ID, the same in every frame; the TIFF description holds spaCR's spacr.lineage/v1 graph (cell names, persistent segment UUIDs and divisions).
• manifest.csv: every frame, its mask and its cell count.
• summary.json: the counts above and how the lineage was converted.

Source

Tracking one-in-a-million, ctc_format sequence 00. https://zenodo.org/records/7260137 (DOI 10.5281/zenodo.7260137).

Frames outside the window are dropped and the rest renumbered from 0; the images and the masks are otherwise unchanged. Each source division with two daughters is a division here, the daughters named after the mother with a and b. A track whose mother is outside the window, or a lone daughter, starts its own lineage.

Built by tools/build_timelapse_example_datasets.py in the spaCR repository.

Licence

CC BY 4.0, as published by the authors. Cite the source below when you use it.

Citation

Seiffarth J, Bloebaum L, Loeffler K, Scherr T, Gruenberger A, Scharr H, Mikut R, Noeh K. Data for - Tracking one-in-a-million: large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics. Zenodo (2022). doi:10.5281/zenodo.7260137