Pith Number

pith:4PE7NJSB

pith:2023:4PE7NJSBSHGH6ILWJLO5SXGU5Y

not attested not anchored not stored refs pending

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma

Adam Flanders, Ahmed W Moawad, Anahita Fathi Kazerooni, Anastasia Janas, Andreas M Rauschecker, Aria Mahtabfar, Ariana Familiar, Arif Rashid, Ayman Nada, Benedikt Wiestler, Bjoern Menze, Chunhao Wang, Collin Kent, Devon Godfrey, Dominic LaBella, Elaine Johanson, Evan Calabrese, Farouk Dako, Fathi Hilal, Florian Kofler, Gian-Marco Conte, Goldey Khanna, Hongwei Bran Li, Ivan Ezhov, Jake Albrecht, James Eddy, Javier Villanueva-Meyer, Jeff Rudie, John Kirkpatrick, John Mongan, Juan Eugenio Iglesias, Keyvan Farahani, Koen Van Leemput, Mariam Aboian, Marie Piraud, Marius George Linguraru, Maruf Adewole, Maxence Pajot, Michelle Alonso-Basanta, Nourel Hoda Tahon, Pierre Nedelec, Pranav Warman, Radhika Bhalerao, Russell Takeshi Shinohara, Ryan McLean, Shan McBurney-Lin, Spyridon Bakas, Sully Chen, Syed Muhammad Anwar, Talissa Altes, Timothy Bergquist, Udunna Anazodo, Ujjwal Baid, Verena Chung, Walter Wiggins, Xinyang Liu, Yury Velichko, Zachary Reitman, Zeke Meier, Zhifan Jiang

arxiv:2305.07642 v1 · 2023-05-12 · cs.CV · cs.AI · cs.LG · stat.ML

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\usepackage{pith}
\pithnumber{4PE7NJSBSHGH6ILWJLO5SXGU5Y}

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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.

Cited by

5 papers in Pith

Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning

Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning

Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis

Receipt and verification

First computed	2026-07-05T06:09:38.870098Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e3c9f6a64191cc7f21764addd95cd4ee0b45887219e9ee0ee24bc3403beedd76

Aliases

arxiv: 2305.07642 · arxiv_version: 2305.07642v1 · doi: 10.48550/arxiv.2305.07642 · pith_short_12: 4PE7NJSBSHGH · pith_short_16: 4PE7NJSBSHGH6ILW · pith_short_8: 4PE7NJSB

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/4PE7NJSBSHGH6ILWJLO5SXGU5Y \
  | 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: e3c9f6a64191cc7f21764addd95cd4ee0b45887219e9ee0ee24bc3403beedd76

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e1078b37652c4da054113bb1be3328627c072c691370b202be37899fca8bcd62",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG",
      "stat.ML"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2023-05-12T17:52:36Z",
    "title_canon_sha256": "b78dcb5ec6860142bd89b615a5f8261c55b633f729a11a76600e8748eaa2a1d7"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2305.07642",
    "kind": "arxiv",
    "version": 1
  }
}