Paper Citation Record · LEDGER

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities

As of 6 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2605.16880.

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pith.paper-citation-record.v1
2605.16880 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T20:52:05.499147Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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verified fuzzy34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d4b78ae-3cd9-4fb1-b250-468dbcefcb42 · outbound

This paper cites Slic superpix- els compared to state-of-the-art superpixel methods.IEEE transactions on pattern analysis and machine intelligence, 34(11):2274–2282.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Slic superpix- els compared to state-of-the-art superpixel methods.IEEE transactions on pattern analysis and machine intelligence, 34(11):2274–2282

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.394413Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8e5a730e-a723-4684-bb01-899138b2ea86 · outbound

This paper cites Smu-net: Style matching u-net for brain tumor segmentation with missing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Smu-net: Style matching u-net for brain tumor segmentation with missing modalities

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.384497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 11620846-31ff-4712-80f1-5d52e1933745 · outbound

This paper cites Robust multimodal brain tumor seg- mentation via feature disentanglement and gated fusion.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Robust multimodal brain tumor seg- mentation via feature disentanglement and gated fusion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.375851Z

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Observation 60062e6b-cb9b-40ea-bda5-a28391ac82c1 · outbound

This paper cites Learning with privileged multimodal knowledge for unimodal segmentation.IEEE transactions on medical imaging, 41(3):621–632.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Learning with privileged multimodal knowledge for unimodal segmentation.IEEE transactions on medical imaging, 41(3):621–632

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.430060Z

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Observation 6c13f212-7bb7-42ae-aec4-db7d58113296 · outbound

This paper cites Rfnet: Region-aware fusion network for incomplete multi-modal brain tumor seg- mentation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Rfnet: Region-aware fusion network for incomplete multi-modal brain tumor seg- mentation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.373870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c5ec0ed5-655f-4b83-9b76-6336b914393e · outbound

This paper cites Hetero-modal variational encoder-decoder for joint modality completion and segmen- tation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Hetero-modal variational encoder-decoder for joint modality completion and segmen- tation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.370060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b39ba2f9-f74a-48c8-baab-b23053c4eb50 · outbound

This paper cites A joint 3d unet-graph neural network-based method for airway seg- mentation from chest cts.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities A joint 3d unet-graph neural network-based method for airway seg- mentation from chest cts

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.386634Z

Source-reported events for the cited work

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Observation 077055df-ef09-403b-aeb1-6f0a3ffa84f9 · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Generative adversarial nets.Advances in neural information processing systems, 27

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.380292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 81d6d0ab-d009-43fc-8ddc-1740cb42ed3f · outbound

This paper cites A new model for learning in graph domains.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities A new model for learning in graph domains

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.392445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8d1a3345-589f-417b-a5ef-2b20c3bb4385 · outbound

This paper cites Hemis: Hetero-modal image segmen- tation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Hemis: Hetero-modal image segmen- tation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.371933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b7beb2cc-d900-48b6-8ea1-690d7858db84 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Distilling the Knowledge in a Neural Network

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:52:46.002152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 951d8086-01b6-41ac-8a2e-4777383ca93f · outbound

This paper cites Knowledge distillation from multi-modal to mono- modal segmentation networks.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Knowledge distillation from multi-modal to mono- modal segmentation networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.396480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2b6eee1c-05ae-4ac2-83b9-3b0c7f2861a5 · outbound

This paper cites Current clinical state of advanced magnetic resonance imaging for brain tumor diagnosis and follow up.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Current clinical state of advanced magnetic resonance imaging for brain tumor diagnosis and follow up

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.365951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 11e4543c-2dff-48cd-bfcb-d9ecea484cab · outbound

This paper cites H 2 nf-net for brain tumor segmentation using multimodal mr imaging: 2nd place solution to brats challenge 2020 segmen- tation task.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities H 2 nf-net for brain tumor segmentation using multimodal mr imaging: 2nd place solution to brats challenge 2020 segmen- tation task

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.363862Z

Source-reported events for the cited work

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Observation 93c38789-3748-4833-8944-58fa5bf9e136 · outbound

This paper cites Two-stage cascaded u-net: 1st place solution to brats challenge 2019 segmentation task.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Two-stage cascaded u-net: 1st place solution to brats challenge 2019 segmentation task

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.367977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 61c0f530-4af9-4936-82de-94dbf673767b · outbound

This paper cites Mmcformer: Missing modality compensation transformer for brain tumor segmentation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Mmcformer: Missing modality compensation transformer for brain tumor segmentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.382389Z

Source-reported events for the cited work

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Observation 186519e5-d4f1-44f8-b28b-19080147da5a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Adam: A Method for Stochastic Optimization

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:52:45.998925Z

Source-reported events for the cited work

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Observation dc65c690-f5ab-443d-a677-43815b1e0553 · outbound

This paper cites Assess- ing the importance of magnetic resonance contrasts using collaborative generative adversarial networks.Nature Ma- chine Intelligence, 2(1):34–42.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Assess- ing the importance of magnetic resonance contrasts using collaborative generative adversarial networks.Nature Ma- chine Intelligence, 2(1):34–42

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.377916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a2dd9429-c5d5-4c76-8b50-b8c5436136e8 · outbound

This paper cites M3ae: multimodal representation learning for brain tumor segmentation with missing modal- ities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities M3ae: multimodal representation learning for brain tumor segmentation with missing modal- ities

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.388653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ea4b763c-9829-4191-9d4c-8ed02c3d1f5e · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:52:46.005897Z

Source-reported events for the cited work

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Observation cdb50f5a-3803-4c73-9873-9253a8b8b7e4 · outbound

This paper cites Dgrunit: Dual graph reason- ing unit for brain tumor segmentation.Computers in biology and medicine, 149:106079.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Dgrunit: Dual graph reason- ing unit for brain tumor segmentation.Computers in biology and medicine, 149:106079

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.426276Z

Source-reported events for the cited work

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Observation a5ad4430-e502-4715-81a0-4cc055ec68d0 · outbound

This paper cites The multimodal brain tumor image segmentation benchmark (brats).IEEE transactions on medical imaging, 34(10):1993–2024.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities The multimodal brain tumor image segmentation benchmark (brats).IEEE transactions on medical imaging, 34(10):1993–2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.422385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8d9dbb6d-021b-4efb-a50d-b4cdfdbcb4ec · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.424370Z

Source-reported events for the cited work

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Observation d9ae7db2-b089-41f2-a25d-b2fc54f9114a · outbound

This paper cites Scratch each other’s back: Incomplete multi-modal brain tumor segmentation via category aware group self-support learning.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Scratch each other’s back: Incomplete multi-modal brain tumor segmentation via category aware group self-support learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.428162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e2035555-72bf-4723-ac84-024165dcf938 · outbound

This paper cites Exploring graph-based neural networks for automatic brain tumor segmentation.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Exploring graph-based neural networks for automatic brain tumor segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.432116Z

Source-reported events for the cited work

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Observation 0fc9a605-5d0c-4067-b1c1-187eca47efdd · outbound

This paper cites Brain tumor segmentation on mri with missing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Brain tumor segmentation on mri with missing modalities

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.414581Z

Source-reported events for the cited work

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Observation 3e1c5a9e-54a9-4d07-b78c-009eeeaef878 · outbound

This paper cites Graph Attention Networks.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Graph Attention Networks

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:52:45.996125Z

Source-reported events for the cited work

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Observation 90ad8985-404a-4fe7-b3da-db50880a3371 · outbound

This paper cites Multi-modal learning with missing modality via shared-specific feature modelling.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Multi-modal learning with missing modality via shared-specific feature modelling

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.410882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b51a15d2-6b7e-46e0-97e6-3f27fcf7db34 · outbound

This paper cites Hypergraph tversky-aware do- main incremental learning for brain tumor segmentation with missing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Hypergraph tversky-aware do- main incremental learning for brain tumor segmentation with missing modalities

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.412779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0e463692-dde0-48fd-892b-29c050a256aa · outbound

This paper cites Acn: adversarial co-training network for brain tumor segmentation with missing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Acn: adversarial co-training network for brain tumor segmentation with missing modalities

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.416465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fe6221af-d3d4-470b-a878-6ee48148cf71 · outbound

This paper cites Brain tissue segmentation based on graph convolutional networks.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Brain tissue segmentation based on graph convolutional networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.406995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 363577ff-9ec4-42bb-8119-537aeef9607b · outbound

This paper cites Learning unified hyper-network for multi-modal mr image synthesis and tu- mor segmentation with missing modalities.IEEE Transac- tions on Medical Imaging, 42(12):3678–3689.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Learning unified hyper-network for multi-modal mr image synthesis and tu- mor segmentation with missing modalities.IEEE Transac- tions on Medical Imaging, 42(12):3678–3689

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.404880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 15975651-5222-4269-a777-76c5f4c4ec1c · outbound

This paper cites Ea-gans: edge-aware genera- tive adversarial networks for cross-modality mr image syn- thesis.IEEE transactions on medical imaging, 38(7):1750– 1762.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Ea-gans: edge-aware genera- tive adversarial networks for cross-modality mr image syn- thesis.IEEE transactions on medical imaging, 38(7):1750– 1762

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.400860Z

Source-reported events for the cited work

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Observation bb219ee1-87cb-45ee-9c50-7d72e35a3092 · outbound

This paper cites an unresolved cited work.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:52:46.390636Z

Source-reported events for the cited work

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Observation 5d8ea331-1e9a-4f6f-b776-f77859bff2b9 · outbound

This paper cites Modality-aware mutual learning for multi-modal medical image segmenta- tion.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Modality-aware mutual learning for multi-modal medical image segmenta- tion

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.420289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d47b4594-72c4-46e3-ac68-17b14b5370fa · outbound

This paper cites mmformer: Multimodal medical transformer for incomplete multimodal learning of brain tumor segmenta- tion.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities mmformer: Multimodal medical transformer for incomplete multimodal learning of brain tumor segmenta- tion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.402797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 05fc40f4-67f5-48cc-a2d6-e6840d924db1 · outbound

This paper cites Tm- former: Token merging transformer for brain tumor seg- mentation with missing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Tm- former: Token merging transformer for brain tumor seg- mentation with missing modalities

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.409025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 883478de-615b-4a51-8651-d313e50711ba · outbound

This paper cites Incomplete multi-modal brain tumor segmentation via learnable sorting state space model.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Incomplete multi-modal brain tumor segmentation via learnable sorting state space model

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.418446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1606d94e-5f46-4b5a-903c-42bd9a28fb81 · outbound

This paper cites Modality-adaptive feature interaction for brain tumor segmentation with miss- ing modalities.

Virtual Nodes Guided Dynamic Graph Neural Network for Brain Tumor Segmentation with Missing Modalities Modality-adaptive feature interaction for brain tumor segmentation with miss- ing modalities

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:52:46.398567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

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