Paper Citation Record · LEDGER

Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2403.14250.

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

pith.paper-citation-record.v1
2403.14250 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:52:01.179577Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5df6bdbf-855a-4707-822b-09debc1c3e46 · inbound

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation cites this paper.

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:52:01.179577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d617747-8f2f-4eab-b9e1-83badd3f04a0 · inbound

MTL-UE: Learning to Learn Nothing for Multi-Task Learning cites this paper.

MTL-UE: Learning to Learn Nothing for Multi-Task Learning Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T23:13:47.346166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54c0a8bb-44ec-446c-9d6d-d50fd4b569ba · inbound

Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking cites this paper.

Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T18:43:06.005117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71fe06e2-739b-48de-a18a-fdbdddeb4d6c · inbound

TopoTTA: Topology-Enhanced Test-Time Adaptation for Tubular Structure Segmentation cites this paper.

TopoTTA: Topology-Enhanced Test-Time Adaptation for Tubular Structure Segmentation Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T10:16:52.295458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bd296af-6aa6-482f-91a0-84ca18dd14d3 · inbound

VoxShield: Protecting 3D Medical Datasets from Unauthorized Training via Frequency-Aware Inter-Slice Disruption cites this paper.

VoxShield: Protecting 3D Medical Datasets from Unauthorized Training via Frequency-Aware Inter-Slice Disruption Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:58:20.133190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8f97a83b-7ebd-4172-9937-b537c6a4b3ec · inbound

DiffUE: Enhancing Utility-Unlearnability Trade-off of Unlearnable Examples via Diffusion Autoencoders cites this paper.

DiffUE: Enhancing Utility-Unlearnability Trade-off of Unlearnable Examples via Diffusion Autoencoders Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T10:41:43.164852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4612335e-ea18-4a0f-93bc-ba8fe6c331bd · inbound

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle cites this paper.

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-08T20:00:15.880801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.