Accession number BBBC004· Version 1
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 consists of five subsets with increasing degree of clustering.
Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with different probabilities in the five subsets. The images were generated with the SIMCEP simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008).
|Overlap probability||Download images|
|0||BBBC004_v1_000_images.zip (13 MB)|
|0.15||BBBC004_v1_015_images.zip (13 MB)|
|0.3||BBBC004_v1_030_images.zip (13 MB)|
|0.45||BBBC004_v1_045_images.zip (13 MB)|
|0.6||BBBC004_v1_060_images.zip (13 MB)|
Each image contains exactly 300 objects; this is the ground truth for counting.
Ground truth for foreground/background segmentation are available as binary images:
|Overlap probability||Download foreground|
|0||BBBC004_v1_000_foreground.zip (469 kB)|
|0.15||BBBC004_v1_015_foreground.zip (440 kB)|
|0.3||BBBC004_v1_030_foreground.zip (433 kB)|
|0.45||BBBC004_v1_045_foreground.zip (421 kB)|
|0.6||BBBC004_v1_060_foreground.zip (401 kB)|
See the TUT Benchmark Set of Synthetic Images for additional materials and examples of usage.
Published results using this image set
"We used image set BBBC004v1 [Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008] from the Broad Bioimage Benchmark Collection [Ljosa et al., Nature Methods, 2012]."