Paper Citation Record · LEDGER

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task

As of 20 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2603.05534.

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

pith.paper-citation-record.v1
2603.05534 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:22:18.472639Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

18 of 18 outbound references displayed

verified exact6
verified fuzzy0
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac09db7e-d85f-475a-9687-d9cf62fc7770 · outbound

This paper cites Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study.Medical Image Analysis, 69: 101952, April 2021.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study.Medical Image Analysis, 69: 101952, April 2021

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.398355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e808cfc-4a5e-453c-9891-b112f819d2ad · outbound

This paper cites Tschuchnig and Michael Gadermayr.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Tschuchnig and Michael Gadermayr

Reference 2

Resolution: verified exact; doi, observed 2026-08-02T19:23:57.722960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 86f63c8b-adec-4c5a-b213-ef4b6b063cd6 · outbound

This paper cites Anomaly detection in brain MRI: a comprehensive review.Biomedical Engineering Letters, January 2026.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Anomaly detection in brain MRI: a comprehensive review.Biomedical Engineering Letters, January 2026

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.407990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aeba8d2-e142-4f10-beb3-43e8f66a30f5 · outbound

This paper cites Unsupervised Anomaly Detection in 3D Brain FDG PET: A Benchmark of 17 V AE-Based Approaches.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Unsupervised Anomaly Detection in 3D Brain FDG PET: A Benchmark of 17 V AE-Based Approaches

Reference 4

Resolution: verified exact; doi, observed 2026-08-02T19:23:57.371398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 44f07afe-d25b-4eb4-be52-4c44abdd2317 · outbound

This paper cites Anomaly Detection for Medical Images Using Heterogeneous Auto-Encoder.IEEE Transactions on Image Processing, 33:2770–2782, 2024.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Anomaly Detection for Medical Images Using Heterogeneous Auto-Encoder.IEEE Transactions on Image Processing, 33:2770–2782, 2024

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.417361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a56df46-401e-4ee9-9f9e-3bf9c6ccfcbd · outbound

This paper cites an unresolved cited work.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.421818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f31188a0-987e-4f95-8219-901488f7c3a1 · outbound

This paper cites Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.426550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dc5b7b7-8418-4ba8-9932-6f9a58220c9c · outbound

This paper cites Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

Reference 8

Resolution: malformed identifier; no resolver link, observed 2026-08-02T19:22:18.431011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d9735c9-d9bc-4eb9-b6ac-887530a33a75 · outbound

This paper cites Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.435168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 384f8e4d-8d1c-42e9-ba90-8dc06c71d7f8 · outbound

This paper cites Sheng, David McAlpine, Paul Sowman, Alexis Giral, and Philip S.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Sheng, David McAlpine, Paul Sowman, Alexis Giral, and Philip S

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.439267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2413b43d-b929-47ae-ba5d-087edef95bf5 · outbound

This paper cites Customized Relationship Graph Neural Network for Brain Disorder Identification.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Customized Relationship Graph Neural Network for Brain Disorder Identification

Reference 11

Resolution: verified exact; doi, observed 2026-08-02T19:23:56.819073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c383018-df2b-4f41-8386-154658611137 · outbound

This paper cites Inter-intra High-Order Brain Network for ASD Diagnosis via Functional MRIs.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Inter-intra High-Order Brain Network for ASD Diagnosis via Functional MRIs

Reference 12

Resolution: verified exact; doi, observed 2026-08-02T19:23:56.383498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71706061-63fe-4147-bb0b-4a72082576a0 · outbound

This paper cites URL https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task URL https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.456542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d16f5cd-f22b-45c1-adbb-ee1d8310da53 · outbound

This paper cites Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images

Reference 14

Resolution: verified exact; doi, observed 2026-08-02T19:23:55.985949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9c1292c3-8654-4fbe-a797-59a646603321 · outbound

This paper cites Waldstein, Georg Langs, and Ursula Schmidt-Erfurth.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Waldstein, Georg Langs, and Ursula Schmidt-Erfurth

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.464882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b3c7510-315c-436c-ad03-2966e499fad1 · outbound

This paper cites MP-DRA: Multi-scale memory and adaptive pseudo-anomaly enhanced open-set anomaly detection.Neurocomputing, 655:131427, November 2025.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task MP-DRA: Multi-scale memory and adaptive pseudo-anomaly enhanced open-set anomaly detection.Neurocomputing, 655:131427, November 2025

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.468778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea75b57f-2733-4675-a9d8-ed258e717c29 · outbound

This paper cites Tri-V AE: Triplet Variational Autoencoder for Unsupervised Anomaly Detection in Brain Tumor MRI.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task Tri-V AE: Triplet Variational Autoencoder for Unsupervised Anomaly Detection in Brain Tumor MRI

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T19:22:18.472639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 328b2353-3dc1-4acf-95ec-45afd7ce3933 · outbound

This paper cites doi:10.24963/ijcai.2024/903.

In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task doi:10.24963/ijcai.2024/903

Reference 8178

Resolution: verified exact; doi, observed 2026-08-02T19:23:57.043231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.