Paper Citation Record · LEDGER

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network

As of 19 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2508.03197.

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

pith.paper-citation-record.v1
2508.03197 v1

Coverage vector

measured 57 of 57 reference resolution

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One-hop event checks from named stored sources.

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measured 1 of 1 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: pith, observed 2026-08-06T04:38:23.237922Z

Reference resolution

57 of 57 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b45ef67-44a8-4ad7-b856-d33f244a8a34 · outbound

This paper cites Choroidal neovas- cularization,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Choroidal neovas- cularization,

Reference 2

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Observation 64b94f93-0db0-4188-88ab-536743c9a34e · outbound

This paper cites Adverse reaction in patients with drug allergy history after simultaneous intravenous fundus fluorescein angiography and indocyanine green angiography,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Adverse reaction in patients with drug allergy history after simultaneous intravenous fundus fluorescein angiography and indocyanine green angiography,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:33.487616Z

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Observation bc28bdab-0e53-48bd-bef5-49f4c8a95ac6 · outbound

This paper cites A review of optical coherence tomography angiography (octa),.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network A review of optical coherence tomography angiography (octa),

Reference 4

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Observation d528a2d1-af96-48a4-a958-9aeff698a878 · outbound

This paper cites Optical coherence tomography angiography in retinal diseases,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Optical coherence tomography angiography in retinal diseases,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:33.051739Z

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Observation 5b31dff9-4f1f-4dfb-bbdc-f30f7e35dc4a · outbound

This paper cites 3d shape modeling and analysis of retinal microvasculature in oct- angiography images,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network 3d shape modeling and analysis of retinal microvasculature in oct- angiography images,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:32.887592Z

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Observation 061ca4e6-a14d-4f9e-ab30-8b4ce27ce9cc · outbound

This paper cites Rethinking dual-stream super-resolution semantic learning in medical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Rethinking dual-stream super-resolution semantic learning in medical image segmentation,

Reference 7

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Observation 23b2b528-cf4f-4e7a-858c-f988babb9c29 · outbound

This paper cites Querying labeled for unlabeled: Cross-image semantic consistency guided semi-supervised semantic segmenta- tion,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Querying labeled for unlabeled: Cross-image semantic consistency guided semi-supervised semantic segmenta- tion,

Reference 8

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Observation e0c142ac-23f3-41c4-8685-7996053afe52 · outbound

This paper cites Automatic quantification of choroidal neovascular- ization lesion area on oct angiography based on density cell-like p systems with active membranes,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Automatic quantification of choroidal neovascular- ization lesion area on oct angiography based on density cell-like p systems with active membranes,

Reference 9

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Observation bb9df9c6-c0ce-4b13-aa8d-4be9a79e6d6f · outbound

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Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Unresolved cited work

Reference 10

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Observation 5402fcb1-fe15-4a83-a650-9e89e19fc7c4 · outbound

This paper cites Automated choroidal neovascularization detec- tion algorithm for optical coherence tomography angiography,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Automated choroidal neovascularization detec- tion algorithm for optical coherence tomography angiography,

Reference 11

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Observation 8533d49d-74a3-45f9-9fe2-ad0d4097e6dd · outbound

This paper cites Automated diagnosis and segmentation of choroidal neovascularization in oct angiography using deep learning,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Automated diagnosis and segmentation of choroidal neovascularization in oct angiography using deep learning,

Reference 12

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Observation ecfd6e4f-f289-43c8-9c37-1cfcb01a1b23 · outbound

This paper cites Rbgnet: Reliable boundary- guided segmentation of choroidal neovascularization,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Rbgnet: Reliable boundary- guided segmentation of choroidal neovascularization,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:31.778551Z

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Observation d32496fd-b0e2-48cb-b2b8-ac0e37e071d4 · outbound

This paper cites Cnv- net: Segmentation, classification and activity score measurement of choroidal neovascularization (cnv) using optical coherence to- mography angiography (octa),.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Cnv- net: Segmentation, classification and activity score measurement of choroidal neovascularization (cnv) using optical coherence to- mography angiography (octa),

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:31.579509Z

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Observation 973cdca9-24e5-4341-a3de-142824023c84 · outbound

This paper cites Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network

Reference 15

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Observation ac8e7a8e-ca59-4d38-b301-717d559848fc · outbound

This paper cites Deep learning for diagnosing and segmenting choroidal neovascularization in oct angiography in a large real-world data set,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Deep learning for diagnosing and segmenting choroidal neovascularization in oct angiography in a large real-world data set,

Reference 16

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Observation 10e38a6e-2c7a-4e8a-9c27-4c1dadf6edf6 · outbound

This paper cites Interactive medical image seg- mentation using deep learning with image-specific fine tuning,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Interactive medical image seg- mentation using deep learning with image-specific fine tuning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:31.040078Z

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Observation e2dc3bf8-ae47-487a-969f-3149a0fa5eb9 · outbound

This paper cites Encoder-decoder with atrous sep- arable convolution for semantic image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Encoder-decoder with atrous sep- arable convolution for semantic image segmentation,

Reference 18

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Observation 23e65046-bd7a-4551-b732-76dc321410df · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Attention U-Net: Learning Where to Look for the Pancreas

Reference 19

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Observation 38028c4f-1b28-4fe5-84f1-1f28c89d720f · outbound

This paper cites Ia-net: informative attention convolu- tional neural network for choroidal neovascularization segmenta- tion in oct images,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Ia-net: informative attention convolu- tional neural network for choroidal neovascularization segmenta- tion in oct images,

Reference 20

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Observation d192c479-3631-4960-b3ea-e49ce2a4b306 · outbound

This paper cites Mf-net: Multi-scale information fusion network for cnv segmentation in retinal OCT images,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Mf-net: Multi-scale information fusion network for cnv segmentation in retinal OCT images,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:30.331934Z

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Observation 351e1534-fed5-4de6-b725-9931b4ac59be · outbound

This paper cites Mpb-cnn: a multi-scale parallel branch cnn for choroidal neovascularization segmentation in sd- oct images,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Mpb-cnn: a multi-scale parallel branch cnn for choroidal neovascularization segmentation in sd- oct images,

Reference 22

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Observation 125ef2d4-1dc4-4211-928f-030d2d884e83 · outbound

This paper cites Au- tomated segmentation of choroidal neovascularization in optical coherence tomography images using multi-scale convolutional neural networks with structure prior,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Au- tomated segmentation of choroidal neovascularization in optical coherence tomography images using multi-scale convolutional neural networks with structure prior,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:29.836003Z

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Observation 10f67f2a-6354-4109-8407-f67185fdeea5 · outbound

This paper cites A comprehensive survey on graph neural networks,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network A comprehensive survey on graph neural networks,

Reference 24

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Observation d67f5767-9b2f-4024-844f-d2b480168d97 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Semi-Supervised Classification with Graph Convolutional Networks

Reference 25

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This paper cites Cnn- enhanced graph convolutional network with pixel-and superpixel- level feature fusion for hyperspectral image classification,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Cnn- enhanced graph convolutional network with pixel-and superpixel- level feature fusion for hyperspectral image classification,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:29.370683Z

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Observation dddd679f-c407-4f23-974d-668d22ccdbe2 · outbound

This paper cites Class-wise dynamic graph convolution for semantic seg- mentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Class-wise dynamic graph convolution for semantic seg- mentation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:29.172634Z

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Observation 5722bd82-47e6-4d25-be1c-905f2b5c7069 · outbound

This paper cites Uncertainty-based graph convolutional networks for organ seg- mentation refinement,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Uncertainty-based graph convolutional networks for organ seg- mentation refinement,

Reference 28

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Observation b1292c2c-739a-48e4-82c5-582978995401 · outbound

This paper cites Attention graph convolution network for image segmentation in big sar imagery data,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Attention graph convolution network for image segmentation in big sar imagery data,

Reference 29

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Observation 3ef6ea13-073e-4a85-9b9a-dd87d659504b · outbound

This paper cites Scale-aware graph neural network for few-shot semantic segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Scale-aware graph neural network for few-shot semantic segmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:28.709773Z

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Observation a57db90e-957e-40e1-928b-b5702bc99a9f · outbound

This paper cites Beyond grids: Learning graph repre- sentations for visual recognition,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Beyond grids: Learning graph repre- sentations for visual recognition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:28.552030Z

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Observation d8ee7d53-4f70-4106-a6b5-6d0d68f3556c · outbound

This paper cites Graph-based global reasoning networks,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Graph-based global reasoning networks,

Reference 32

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Observation c3ce6886-998e-4b82-8c19-73ad2184f9ec · outbound

This paper cites Referring image segmentation via cross-modal progressive comprehension,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Referring image segmentation via cross-modal progressive comprehension,

Reference 33

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Observation ca5b98b9-b9f9-4a4c-a8b6-7b088badc8e9 · outbound

This paper cites Dual Graph Convolutional Network for Semantic Segmentation.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Dual Graph Convolutional Network for Semantic Segmentation

Reference 34

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Observation f92d05b9-052a-4bf2-b423-9a2516ff6944 · outbound

This paper cites Deep vessel segmentation by learning graphical connectiv- ity,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Deep vessel segmentation by learning graphical connectiv- ity,

Reference 35

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This paper cites Ginet: Graph interaction network for scene parsing,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Ginet: Graph interaction network for scene parsing,

Reference 36

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Observation caeabf86-d214-487c-9378-f0f122f325e1 · outbound

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Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Unresolved cited work

Reference 37

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Observation 68c8fd59-e8eb-41f5-85b2-52e528cae2cc · outbound

This paper cites Multiple-Human Parsing in the Wild.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Multiple-Human Parsing in the Wild

Reference 38

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Observation 517a9494-5c82-4daa-a937-04f7230386b2 · outbound

This paper cites Pedestrian at- tribute recognition by joint visual-semantic reasoning and knowl- edge distillation.,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Pedestrian at- tribute recognition by joint visual-semantic reasoning and knowl- edge distillation.,

Reference 39

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Observation f45cae4c-8260-439c-8f70-238dfc945b9c · outbound

This paper cites Graph-bas3net: Boundary-aware semi-supervised segmentation network with bilateral graph convolution,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Graph-bas3net: Boundary-aware semi-supervised segmentation network with bilateral graph convolution,

Reference 40

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Observation 5bd14d37-349e-48da-82d7-fc53f08e1a42 · outbound

This paper cites U2-net: Going deeper with nested u-structure for salient object detection,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network U2-net: Going deeper with nested u-structure for salient object detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:26.438120Z

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Observation 06a915bd-1a3a-4956-94e7-b27c47a216e6 · outbound

This paper cites A computational approach to edge detection,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network A computational approach to edge detection,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:26.181711Z

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Observation 24907920-dba2-4aab-b338-046400b23ddb · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Deepsdf: Learning continuous signed distance functions for shape representation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:25.823680Z

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Observation 3cf0290e-feaa-44a4-83d4-ffc7c7c1287b · outbound

This paper cites Fronts propagating with curvature- dependent speed: algorithms based on Hamilton-Jacobi formula- tions,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Fronts propagating with curvature- dependent speed: algorithms based on Hamilton-Jacobi formula- tions,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:25.605380Z

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Observation 8b8fca3c-a648-4c71-a822-44525e58dbfb · outbound

This paper cites Shape-aware organ segmentation by predicting signed distance maps,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Shape-aware organ segmentation by predicting signed distance maps,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:25.286461Z

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Observation dda1579c-9b8e-4916-abfb-355a177a1aec · outbound

This paper cites Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

Reference 46

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This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network U-net: Convolutional networks for biomedical image segmentation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:25.164151Z

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Observation faf39541-2eab-4d13-bbac-4ffef504ff5b · outbound

This paper cites Ce- net: Context encoder network for 2d medical image segmenta- tion,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Ce- net: Context encoder network for 2d medical image segmenta- tion,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.962567Z

Source-reported events for the cited work

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Observation 77a3ae81-ab6d-4fa4-aaea-9272bd86387e · outbound

This paper cites Cs- net: channel and spatial attention network for curvilinear structure segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Cs- net: channel and spatial attention network for curvilinear structure segmentation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.822157Z

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Observation 8ec4657f-4d26-48ed-812f-815c78151c1d · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T04:38:21.491793Z

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Observation 26bfec4b-0489-4038-b989-7be8f5ecc3d8 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Swin-unet: Unet-like pure transformer for medical image segmentation,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.722747Z

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Observation cab9a72f-e0d6-4534-8f48-ca5f20045fd4 · outbound

This paper cites H2former: An efficient hierarchical hybrid trans- former for medical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network H2former: An efficient hierarchical hybrid trans- former for medical image segmentation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.605769Z

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Observation e676302c-b3d7-4406-8e27-149f1f46b4fe · outbound

This paper cites Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T04:38:21.969197Z

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Observation ca1254ec-e060-4edc-bb5f-c7ae0ebb1f54 · outbound

This paper cites Graph-based region and boundary aggregation for biomedical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Graph-based region and boundary aggregation for biomedical image segmentation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.389009Z

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Observation 4c22585d-d521-45f8-88cc-8998495bf01d · outbound

This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:24.208986Z

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Observation 707af116-b4ed-4c9d-8a16-9d08ddd397c8 · outbound

This paper cites Diversified and personalized multi-rater medical image segmentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Diversified and personalized multi-rater medical image segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:23.994159Z

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Observation 082b96b8-e06d-4ae8-b492-6aa2d5cb0034 · outbound

This paper cites Multi-view aggregation network for dichotomous image seg- mentation,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Multi-view aggregation network for dichotomous image seg- mentation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:23.842144Z

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Observation f7bf4cb3-9cc7-4549-b237-c3339b726b2a · outbound

This paper cites Towards au- tomatic polyp detection with a polyp appearance model,.

Neovascularization Segmentation via a Multilateral Interaction-Enhanced Graph Convolutional Network Towards au- tomatic polyp detection with a polyp appearance model,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T04:38:23.607749Z

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Pith citing papers

Observation 973cdca9-24e5-4341-a3de-142824023c84 · inbound