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Paper Citation Record · LEDGER

High-Fidelity 3D Geometric Reconstruction of Pelvic Organs from MRI: A Hybrid Deep Learning and Iterative Optimization Approach

As of 11 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 0 inbound Pith citation observations for arXiv:2606.17836.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.17836 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T01:52:54.373961Z

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

3 of 3 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2345a517-efbc-4481-b721-4167d9fff176 · outbound

This paper cites From Pixels to Polygons: A Survey of Deep Learning Approaches for Medical Image-to-Mesh Reconstruction.

High-Fidelity 3D Geometric Reconstruction of Pelvic Organs from MRI: A Hybrid Deep Learning and Iterative Optimization Approach From Pixels to Polygons: A Survey of Deep Learning Approaches for Medical Image-to-Mesh Reconstruction

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:18:55.061851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-27T01:52:54.373961Z digest=sha256:70dc8451179fd555c8a4e1a3db02a0cdba7bd311cd88c5549432f6a9fb6bdeb1

Observation 50d9c2c4-057c-4116-b670-a53b27a08770 · outbound

This paper cites Attention Is All You Need.

High-Fidelity 3D Geometric Reconstruction of Pelvic Organs from MRI: A Hybrid Deep Learning and Iterative Optimization Approach Attention Is All You Need

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-03T19:18:55.059148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-27T01:52:54.373961Z digest=sha256:6e0a7238353ce007a9017c1ee66dadb23b5a87c49d95ccbfb0163430a2580acf

Observation 0e38b5cf-cbba-4b5f-8fc2-46ce905d8301 · outbound

This paper cites an unresolved cited work.

High-Fidelity 3D Geometric Reconstruction of Pelvic Organs from MRI: A Hybrid Deep Learning and Iterative Optimization Approach Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-06-27T01:52:54.373961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T01:52:54.373961Z digest=sha256:1a2a968333e93f9454d9813a8c06f5ef08f11a36fbf18c4f0d27504337572043

Pith citing papers

No inbound Pith citation observations are available.