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Visible Human Project: MRI of the head

pl.load("visible_human_head_mri") loads this dataset. Head MRI from the NLM Visible Human Project, as distributed with the SimpleITK notebooks. Small (2 MB), ideal for a first segmentation.

import pardesline as pl

ds = pl.load("visible_human_head_mri")
print(ds.describe())  # roles, frames, units, labels, licence, citation
s = ds[0]
obj = s.mri  # fetched now, cached under ~/.cache/pardesline/datasets/visible_human_head_mri

Provenance and licence
Source direct HTTPS downloads with checksums: vm_head_mri.mha
Scheme https
Size of the whole source 2 MB
Licence not a standard licence: see the note
Redistribution unknown
Licence note NLM Visible Human Project data; free since 2019 under NLM terms. Terms of use TO CONFIRM with the data owner before any redistribution.
Terms https://www.nlm.nih.gov/research/visible/visible_human.html
Homepage https://www.nlm.nih.gov/research/visible/visible_human.html
Cite Ackerman M.J. The Visible Human Project. Proc. IEEE 86(3), 1998.
Samples grouped by file
Samples listed in the manifest 1

Roles (what each sample contains)

Role Type Frame Units Labels / layout Pattern or file
mri volume (MR) from the file header from the file header vm_head_mri.mha
Head MRI

Standardized layout

Files are fetched on first access into the dataset cache and stay in their original format; ds.export(folder) writes every sample as standard files (PLY for points and meshes, MetaImage for volumes and label maps) with a .pardesline.json sidecar carrying frame, units, labels, licence and provenance, plus a manifest for the folder. Label maps become exact surfaces with to_mesh(label=k), DICOM series become one volume, raw arrays are decoded through the layout above.

ds = pl.load("visible_human_head_mri").take(2)
ds.export("./standardized")        # PLY / MetaImage + sidecars + manifest.json

Algorithms and models that run on it

Generated from src/pardesline/data/manifests/visible_human_head_mri.json on 2026-10-10.