Paper Citation Record · LEDGER

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2

As of 23 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2507.19282.

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

pith.paper-citation-record.v1
2507.19282 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:58:57.117570Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

7 of 7 outbound references displayed

verified exact0
verified fuzzy4
unresolved2
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0b37008e-9252-430b-8c4b-cb76911c43e3 · outbound

This paper cites It is a highly effective treatment; however, its success relies on accurate tumor localization and delineation.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 It is a highly effective treatment; however, its success relies on accurate tumor localization and delineation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:58:57.216428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f6ad2c8c-62d0-464c-9cd5-c6345931b211 · outbound

This paper cites Data augmentation helps alleviate this by synthetically increasing data diversity [36].

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 Data augmentation helps alleviate this by synthetically increasing data diversity [36]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:58:57.205167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 52697369-558d-4aaa-b439-560a2d38e08a · outbound

This paper cites The overall architecture of SAM2-Aug is illustrated in Figure 3.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 The overall architecture of SAM2-Aug is illustrated in Figure 3

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:58:57.193869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b8e43198-f10b-4950-8f13-09cf37e1b7fd · outbound

This paper cites an unresolved cited work.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-15T17:58:57.182835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f1ea5bd2-67dc-4b75-99d1-fabd252516b0 · outbound

This paper cites an unresolved cited work.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 Unresolved cited work

Reference 5

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T17:58:57.171700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 73afa134-ef74-4728-8eaa-93bd305ad40e · outbound

This paper cites We found that simple input and prompt augmentations are effective strategies for improving tumor segmentation performance in ART.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 We found that simple input and prompt augmentations are effective strategies for improving tumor segmentation performance in ART

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T17:58:57.160617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3bc5de3f-a477-475f-99f3-12d3b5432765 · outbound

This paper cites SAM-Med2D.

SAM2-Aug: Prior knowledge-based Augmentation for Target Volume Auto-Segmentation in Adaptive Radiation Therapy Using Segment Anything Model 2 SAM-Med2D

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T17:58:57.117570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.