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Paper Citation Record · LEDGER

Real-time photoacoustic projection imaging using deep learning

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1801.06693.

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

pith.paper-citation-record.v1
1801.06693 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:49:14.596305Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T15:37:09.856940Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9815f86f-2ef5-4159-9695-a4bb03d58b95 · inbound

Learned backprojection for sparse and limited view photoacoustic tomography cites this paper.

Learned backprojection for sparse and limited view photoacoustic tomography Real-time photoacoustic projection imaging using deep learning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T15:49:14.596305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:49:14.596305Z digest=sha256:71628668245e1ba80dced060f95ab69e9758a1cf2522e5c9eedf7a7215efe43b

Observation 552fd498-29d8-410e-9a77-6c334d3cb8b2 · inbound

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo cites this paper.

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo Real-time photoacoustic projection imaging using deep learning

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-14T15:37:09.862639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T15:37:08.743942Z digest=sha256:d8b9d504f5af688edac7ce7f576c02911c5a081273aec667c90ab4e47e1826b3