Pith Number

pith:YR5WIBWU

pith:2026:YR5WIBWUNVEIXWW77SEXREVRNU

not attested not anchored not stored refs pending

Tracing Like a Clinician: Anatomy-Guided Spatial Priors for Cephalometric Landmark Detection

Pallavi Mohanty, Sidhartha Mohapatra

Translating orthodontists' tracing workflow into anatomy-guided spatial priors improves landmark detection accuracy and generalization across imaging devices.

arxiv:2605.03358 v2 · 2026-05-05 · cs.CV

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\usepackage{pith}
\pithnumber{YR5WIBWUNVEIXWW77SEXREVRNU}

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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

On 1,502 radiographs from three sources spanning 7+ imaging devices, the system achieves 1.04 mm mean radial error on 25 landmarks -- surpassing prior state-of-the-art (1.23 mm on 19 landmarks) by 15.4%, with twelve landmarks below 1 mm. A three-way controlled ablation reveals that removing anatomical priors destroys generalization: both models converge to ~1.03 mm on validation, but diverge to 1.94 vs. 1.04 mm on the test set.

C2weakest assumption

That the five-phase pipeline faithfully and without bias translates the clinician's structured workflow (soft tissue identification, region partitioning, contour tracing, geometric landmark definitions) into accurate confidence-weighted spatial priors that remain valid across diverse imaging devices and patient populations.

C3one line summary

An anatomy-guided five-phase initialization pipeline encodes clinical workflow as spatial priors for HRNet-W32, achieving 1.04 mm mean radial error on 25 cephalometric landmarks across 1502 radiographs and outperforming prior SOTA by 15.4% while demonstrating superior generalization in ablations.

Receipt and verification

First computed	2026-05-26T01:03:31.925633Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c47b6406d46d488bdadffc897892b16d1a06a88ac0cc1b4a8cf59c1fc074a209

Aliases

arxiv: 2605.03358 · arxiv_version: 2605.03358v2 · doi: 10.48550/arxiv.2605.03358 · pith_short_12: YR5WIBWUNVEI · pith_short_16: YR5WIBWUNVEIXWW7 · pith_short_8: YR5WIBWU

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/YR5WIBWUNVEIXWW77SEXREVRNU \
  | 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: c47b6406d46d488bdadffc897892b16d1a06a88ac0cc1b4a8cf59c1fc074a209

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e3d8dbe173745571ab06c52793189027c0387ba071d6bbfc702a578d45d7d565",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-05T04:33:45Z",
    "title_canon_sha256": "9ac22f319294e5c81ea9229e92ca058f618ebf1b4534439c43a04e75c590597d"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.03358",
    "kind": "arxiv",
    "version": 2
  }
}