Paper Citation Record · LEDGER

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2502.03825.

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

pith.paper-citation-record.v1
2502.03825 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:39:02.386355Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

20 of 20 outbound references displayed

verified exact1
verified fuzzy9
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e146491a-fece-4cec-9b71-6ce90bfe8b2c · outbound

This paper cites Gan-based synthetic brain mr image generation.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Gan-based synthetic brain mr image generation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.912697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fdee0759-2e76-4246-b26a-179c91212743 · outbound

This paper cites Synthetic Data in AI: Challenges, Applications, and Ethical Implications.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Synthetic Data in AI: Challenges, Applications, and Ethical Implications

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.324847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b16d3f-f58e-42fd-89f2-313fc436539e · outbound

This paper cites A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.329823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 816ac312-8076-4ee5-9b8c-e8dfb186120c · outbound

This paper cites A mul- timodal feature distillation with cnn-transformer network for brain tumor segmentation with in- complete modalities.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation A mul- timodal feature distillation with cnn-transformer network for brain tumor segmentation with in- complete modalities

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.335052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6848c9e9-85f9-443c-af92-c1577a28a07a · outbound

This paper cites Auto-Encoding Variational Bayes.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Auto-Encoding Variational Bayes

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.340271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aff66a3-9e7e-48ce-84c4-9b778427cf36 · outbound

This paper cites SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.344947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b568381-07ce-4460-9f75-f602e4d42711 · outbound

This paper cites Data poi- soning attacks over diabetic retinopathy images classification.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Data poi- soning attacks over diabetic retinopathy images classification

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.867849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f56cb82b-b74f-406d-a96a-eec284779b8d · outbound

This paper cites The multimodal brain tumor image segmentation benchmark (brats).

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation The multimodal brain tumor image segmentation benchmark (brats)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.853262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d97c47ce-2861-4592-ba36-89beb6d48bbe · outbound

This paper cites Conditional Generative Adversarial Nets.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Conditional Generative Adversarial Nets

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.363668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1804c56-9c52-459e-b476-b30b87fa3f9c · outbound

This paper cites U-net: Convolutional networks for biomed- ical image segmentation.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation U-net: Convolutional networks for biomed- ical image segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.823469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 361fe1ed-6ee7-4134-97ff-0a6d1da0fc53 · outbound

This paper cites A Survey on Trustworthiness in Foundation Models for Medical Image Analysis.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation A Survey on Trustworthiness in Foundation Models for Medical Image Analysis

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.377249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c67ad9-b364-461b-b8ba-5cfda180cfa4 · outbound

This paper cites Intriguing properties of neural networks.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Intriguing properties of neural networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.381838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39f6fe60-8d03-44c2-870d-b208814bfd9b · outbound

This paper cites Medical image synthesis with context-aware generative adversarial networks.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Medical image synthesis with context-aware generative adversarial networks

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.838039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 036760f0-61f3-43c6-938e-4a8c07b90d02 · outbound

This paper cites Robust machine learning systems: Reliability and security for deep neural networks.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Robust machine learning systems: Reliability and security for deep neural networks

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.898727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 79f9844a-9c3d-430b-a003-87576dced5da · outbound

This paper cites A survey on data poisoning attacks and defenses.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation A survey on data poisoning attacks and defenses

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.926530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6d93ccdd-2256-4c5b-8ec2-ee87c24e2294 · outbound

This paper cites Active learning under malicious mislabeling and poisoning attacks.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Active learning under malicious mislabeling and poisoning attacks

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.883622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5406918e-998a-469e-a9c8-ad337e259913 · outbound

This paper cites Trustworthy Deep Learning for Medical Image Segmentation.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Trustworthy Deep Learning for Medical Image Segmentation

Reference 2022

Resolution: verified exact; local_arxiv, observed 2026-08-09T00:39:02.776345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9b274567-d45c-4fa0-863a-e2c07d94652b · outbound

This paper cites PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.309959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08380009-3003-4cab-a738-d4b71c6c5adb · outbound

This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T00:39:02.294021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d51315-05ec-48a1-bc83-b84ed9653ce0 · outbound

This paper cites Data poisoning attacks against federated learning systems.

Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation Data poisoning attacks against federated learning systems

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:39:02.807513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.