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2018 Data Science Bowl (BBBC038) - Nuclei Segmentation
2D light-microscopy cell-nucleus segmentation assembled across many imaging experiments (humans, mice, flies; 22 cell types, 15 resolutions, 30+ experiments). The collection deliberately spans multiple modalities: fluorescence (DAPI / Hoechst), brightfield H&E histopathology, and other brightfield - making it a standard cross-modality nuclei-segmentation benchmark.
This is the official BBBC038v1 release (Broad Bioimage Benchmark Collection), the same data used in the Kaggle 2018 Data Science Bowl. License: CC0 / public domain.
Contents & splits
| Split | Images | Nuclei | Ground-truth source |
|---|---|---|---|
train (stage1_train) |
670 | 29,461 | native per-nucleus PNG instance masks |
stage1_test (stage1_test) |
65 | 4,152 | RLE in stage1_solution.csv (post-competition) |
stage2_test (stage2_test) |
106 | 3,716 | RLE in stage2_solution_final.csv (post-competition) |
| Total | 841 | 37,329 |
Faithful-naming notes
- Most papers cite "DSB2018" =
stage1_train(670) only, since that is the only split distributing native instance masks. This repo ships the full 3-stage set; the test-stage GT was decoded from the official solution-CSV RLE. - The raw
stage2_test_finalarchive contains ~3,019 images, but only 106 are scored - the rest are intentional decoys flaggedUsage=Ignored. Only the 106 scored images are included here.
Ground truth
mask is a binary semantic nucleus mask (mode L, values {0, 255}): the
union of all per-nucleus instances. For train it is the union of the native
per-nucleus PNG masks; for the test splits it is the union of the RLE-decoded
nuclei. The RLE decoder was validated against the native train masks
(pixel agreement = 1.000000). The original per-nucleus instance masks remain
available at BBBC038 for
instance-segmentation use.
Columns
| Column | Type | Notes |
|---|---|---|
image_id |
string | source hash id |
image |
Image | RGB (RGBA fluorescence normalized to RGB) |
mask |
Image | binary semantic, {0,255} |
split |
string | stage1_train / stage1_test / stage2_test |
num_nuclei |
int32 | nuclei in this image |
height,width |
int32 | image dimensions |
usage |
string | null (train) / Public (s1) / Private (s2) |
is_grayscale |
bool | derived (R==G==B): fluorescence/brightfield vs H&E color |
metadata.xlsx (repo root) is the official 43-row per-experiment provenance table
(cell type, stain, SNR, resolution).
Provenance, overlap & integrity
- Provenance: official BBBC038v1 (Broad Institute), CC0. Counts reconcile with the paper (670 / 65 / 106).
- Overlap (leakage hazards): a small fraction of images overlap BBBC039. The H&E subset shares source-level (TCGA-derived) lineage with H&E nuclei sets such as MoNuSeg / PanNuke, though no individually-confirmed shared images.
- Curated collection: assembled from 30+ independent experiments / donor labs.
Citation
Caicedo, J.C., Goodman, A., Karhohs, K.W., et al. Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl. Nature Methods 16(12), 1247-1253 (2019). doi:10.1038/s41592-019-0612-7
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