3D Colon Tissue (synthetic data)

Accession number BBBC027 · Version 1

Example images

  • In focus
    3D image
  • Out of focus
    3D foreground

Biological application

One of the principal challenges in counting or segmenting nuclei is dealing with clustered nuclei. To help assess algorithms' performance in this regard, this synthetic image set is provided in two diferent levels of quality: high SNR and low SNR.

Images

A set (both in high and low SNR variant) of 30 images is provided. Each image contains the collection of nuclei formed in clusters. The dataset was generated using the virtual microscope imitating the microscope Zeiss S100 (objective Zeiss 63x/1.40 Oil DIC) attached to confocal unit Atto CARV and CCD camera Micromax 1300-YHS.

SNR download images
low BBBC027_lowSNR_images_part1.zip
low BBBC027_lowSNR_images_part2.zip
low BBBC027_lowSNR_images_part3.zip
high BBBC027_highSNR_images_part1.zip
high BBBC027_highSNR_images_part2.zip
high BBBC027_highSNR_images_part3.zip

Ground truth (C) (F)

Each image contains binary mask of all the cells located inside the ROI; this is the ground truth for counting. Ground truth for foreground/background segmentation are available as binary images:

SNR download foreground
low BBBC027_lowSNR_foreground_part1.zip
low BBBC027_lowSNR_foreground_part2.zip
low BBBC027_lowSNR_foreground_part3.zip
high BBBC027_highSNR_foreground_part1.zip
high BBBC027_highSNR_foreground_part2.zip
high BBBC027_highSNR_foreground_part3.zip

Recommended citation

"We used image set BBBC027 [Svoboda David, Homola Ondřej, Stejskal Stanislav. Generation of 3D Digital Phantoms of Colon Tissue, In International Conference on Image Analysis and Recognition - ICIAR 2011, Part II, LNCS 6754, Berlin, Heidelberg: Springer-Verlag, pp 31-39, June 2011] from the Broad Bioimage Benchmark Collection."

Copyright

Creative Commons License The images and ground truth are licensed under a Creative Commons Attribution 3.0 Unported License by David Svoboda.

This page last updated 2015-10-06