Pith Number

pith:TC57MHUK

pith:2026:TC57MHUKDXBZFIIWYPS4HWNHMQ

not attested not anchored not stored refs resolved

Automatic Landmark-Based Segmentation of Human Subcortical Structures in MRI

Ahmed Rekik, Linda Marrakchi-Kacem, R. Jarrett Rushmore, Sylvain Bouix

A landmark-guided method segments subcortical brain structures in MRI by first detecting 16 reference points, producing coarse labels, and then splitting them into 26 precise structures to match manual protocols.

arxiv:2605.14221 v1 · 2026-05-14 · cs.CV

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\usepackage{pith}
\pithnumber{TC57MHUKDXBZFIIWYPS4HWNHMQ}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Experimental results demonstrate consistent improvements in boundary accuracy by integrating learned landmarks that align segmentations more closely with manual protocols.

C2weakest assumption

The assumption that automatically detected landmarks can reliably enforce local anatomical constraints to separate coarse labels into distinct structures without errors in varied MRI data.

C3one line summary

A three-stage pipeline detects 16 landmarks, coarsely segments 12 labels, and refines them into 26 structures using landmark constraints to improve accuracy in subcortical MRI segmentation.

References

17 extracted · 17 resolved · 1 Pith anchors

[1] B. Fischl, “FreeSurfer,”NeuroImage, vol. 62, no. 2, pp. 774–781, 2012 2012

[2] A Bayesian model of shape and appearance for subcortical brain segmen- tation, 2011

[3] Multi-atlas segmentation of biomedi- cal images: A survey, 2015

[4] U-Net: Convolutional net- works for biomedical image segmentation, 2015

[5] TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation 2021 · arXiv:2102.04306

Receipt and verification

First computed	2026-05-17T23:39:10.821953Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

98bbf61e8a1dc392a116c3e5c3d9a7640455e05b3d2aa9a2ee5de66a66c13caa

Aliases

arxiv: 2605.14221 · arxiv_version: 2605.14221v1 · doi: 10.48550/arxiv.2605.14221 · pith_short_12: TC57MHUKDXBZ · pith_short_16: TC57MHUKDXBZFIIW · pith_short_8: TC57MHUK

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/TC57MHUKDXBZFIIWYPS4HWNHMQ \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 98bbf61e8a1dc392a116c3e5c3d9a7640455e05b3d2aa9a2ee5de66a66c13caa

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "24c8dad4b98ba108e8a6bfc7ded30459e4b730af55babfe43d9c670c5ff2c392",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-14T00:31:02Z",
    "title_canon_sha256": "85eca1692bc90244af1cda8455cfb859d57c156d75cea1278f20dee7b7f31d37"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14221",
    "kind": "arxiv",
    "version": 1
  }
}