Pith Number

pith:2BXWGSKT

pith:2026:2BXWGSKTAHIE4PALOA3RC7X6RF

not attested not anchored not stored refs resolved

Diffeomorphic Cortical Alignment via Direct Warping of Streamline Endpoints

Martin Cole, Yang Xiang, Zhengwu Zhang

Aligning cortical surfaces by directly warping white-matter tract endpoints on a product manifold improves fiber bundle correspondence.

arxiv:2605.16742 v1 · 2026-05-16 · cs.CV · stat.ME

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\pithnumber{2BXWGSKTAHIE4PALOA3RC7X6RF}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

Experiments on HCP data demonstrate improved tract-level correspondence, achieving higher connectivity-level overlap coefficients on major fiber bundles and stronger robustness across grid resolutions for Ω compared to state-of-the-art methods such as ENCORE and MSMAll.

C2weakest assumption

That operating directly on tract endpoints modeled as a point cloud on the product manifold Ω × Ω and minimizing connectivity mismatch via iterative diffeomorphic warps produces anatomically valid alignments that respect long-range white-matter constraints without introducing artifacts from tractography estimation.

C3one line summary

Presents a diffeomorphic cortical surface registration technique that iteratively warps streamline endpoints on the product manifold to optimize tract-level correspondence using HCP data.

References

29 extracted · 29 resolved · 0 Pith anchors

[1] arXiv preprint arXiv:2503.15830 , year=

[2] Recognition of white matter bundles using local and global streamline-based registration and clustering , author=. NeuroImage , volume=. 2018 , publisher= 2018

[3] Nature Communications , volume= 2017

[4] Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review , author=. Neuroimage , volume=. 2022 , publisher= 2022

[5] Deep-Learning Cortical Registration Guided by Structural and Diffusion MRI and Connectivity , author=. bioRxiv , pages=

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:02:39.329928Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d06f63495301d04e3c0b7037117efe8950d4a267739b1df65704e06f3d71993f

Aliases

arxiv: 2605.16742 · arxiv_version: 2605.16742v1 · doi: 10.48550/arxiv.2605.16742 · pith_short_12: 2BXWGSKTAHIE · pith_short_16: 2BXWGSKTAHIE4PAL · pith_short_8: 2BXWGSKT

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/2BXWGSKTAHIE4PALOA3RC7X6RF \
  | 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: d06f63495301d04e3c0b7037117efe8950d4a267739b1df65704e06f3d71993f

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "3311370183325ef32abd5a9b0096a097cff1d5a98961719211877866087cb94e",
    "cross_cats_sorted": [
      "stat.ME"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-16T01:46:32Z",
    "title_canon_sha256": "e6985f4a9d01fdfd9e2ca96ce367797eb36082b1cf159accc50030e291d89f68"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16742",
    "kind": "arxiv",
    "version": 1
  }
}