Imaging Mass Cytometry
Human kidney
S-BIAD3694:discovery:Batch18:L112:kidney
bronze ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'img_Batch18_007_image': DataTree[cyx] (35, 1458, 656), (35, 729, 328), (35, 364, 164), (35, 182, 82), (35, 91, 41)
│ ├── 'img_Batch18_008_image': DataTree[cyx] (35, 1159, 659), (35, 579, 329), (35, 289, 164), (35, 144, 82), (35, 72, 41)
│ ├── 'img_Batch18_009_image': DataTree[cyx] (35, 1989, 704), (35, 994, 352), (35, 497, 176), (35, 248, 88), (35, 124, 44)
│ ├── 'img_Batch18_010_image': DataTree[cyx] (35, 1164, 561), (35, 582, 280), (35, 291, 140), (35, 145, 70), (35, 72, 35)
│ └── 'img_Batch18_011_image': DataTree[cyx] (35, 3397, 589), (35, 1698, 294), (35, 849, 147), (35, 424, 73), (35, 212, 36)
├── Labels
│ ├── 'img_Batch18_007_cells_labels': DataTree[yx] (1458, 656), (729, 328), (364, 164), (182, 82), (91, 41)
│ ├── 'img_Batch18_008_cells_labels': DataTree[yx] (1159, 659), (579, 329), (289, 164), (144, 82), (72, 41)
│ ├── 'img_Batch18_009_cells_labels': DataTree[yx] (1989, 704), (994, 352), (497, 176), (248, 88), (124, 44)
│ ├── 'img_Batch18_010_cells_labels': DataTree[yx] (1164, 561), (582, 280), (291, 140), (145, 70), (72, 35)
│ └── 'img_Batch18_011_cells_labels': DataTree[yx] (3397, 589), (1698, 294), (849, 147), (424, 73), (212, 36)
├── Shapes
│ ├── 'img_Batch18_007_cell_boundaries': GeoDataFrame shape: (1942, 2) (2D shapes)
│ ├── 'img_Batch18_008_cell_boundaries': GeoDataFrame shape: (1695, 2) (2D shapes)
│ ├── 'img_Batch18_009_cell_boundaries': GeoDataFrame shape: (3408, 2) (2D shapes)
│ ├── 'img_Batch18_010_cell_boundaries': GeoDataFrame shape: (1754, 2) (2D shapes)
│ └── 'img_Batch18_011_cell_boundaries': GeoDataFrame shape: (4641, 2) (2D shapes)
└── Tables
└── 'table': AnnData (13440, 35)
with coordinate systems:
▸ 'img_Batch18_007', with elements:
img_Batch18_007_image (Images), img_Batch18_007_cells_labels (Labels), img_Batch18_007_cell_boundaries (Shapes)
▸ 'img_Batch18_008', with elements:
img_Batch18_008_image (Images), img_Batch18_008_cells_labels (Labels), img_Batch18_008_cell_boundaries (Shapes)
▸ 'img_Batch18_009', with elements:
img_Batch18_009_image (Images), img_Batch18_009_cells_labels (Labels), img_Batch18_009_cell_boundaries (Shapes)
▸ 'img_Batch18_010', with elements:
img_Batch18_010_image (Images), img_Batch18_010_cells_labels (Labels), img_Batch18_010_cell_boundaries (Shapes)
▸ 'img_Batch18_011', with elements:
img_Batch18_011_image (Images), img_Batch18_011_cells_labels (Labels), img_Batch18_011_cell_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("L0h6fVrvxDiceP4e0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("L0h6fVrvxDiceP4e") # stem uid: Lamin resolves it to the latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Shell
# sddb client: download the .zarr into data/
sddb-cli download L0h6fVrvxDiceP4e0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/L0h6fVrvxDiceP4e
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid L0h6fVrvxDiceP4eLicense: CC0 1.0
Metadata
- Technology
- Imaging Mass Cytometry
- Organism
- human
- Tissue
- kidney
- Modality
- protein
- Observations (cells)
- 13,440
- Tier
- bronze
- Chemistry
- IMC
- Staining
- Antibodies
- Size
- 150 MB
- Sample ID
- S-BIAD3694:discovery:Batch18:L112:kidney
- License
- CC0 1.0
- Published
- Aug 18, 2026
Cite this dataset
doi.org/10.1038/s41467-026-77210-y ↗ BibTeX
@article{bia:S-BIAD3694,
doi = {10.1038/s41467-026-77210-y},
title = {S-BIAD3694:discovery:Batch2:L108:kidney}
}Source: BioImage Archive ↗ · License: CC0 1.0 ↗ · Reprocessed to SpatialData by SpatialData-DB