Paper Citation Record · LEDGER

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation

As of 20 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2504.13599.

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pith.paper-citation-record.v1
2504.13599 v1

Coverage vector

measured 50 of 50 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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A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-16T12:08:26.535372Z

Reference resolution

50 of 50 outbound references displayed

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External citation measurements

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Outbound references

Observation 414f23be-05df-4592-b615-48a0069c5b4a · outbound

This paper cites It consists of 40 annotated Cardiac CTA images with an initial resolution of 512× 512× N , where N ranges from 168 to 334.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation It consists of 40 annotated Cardiac CTA images with an initial resolution of 512× 512× N , where N ranges from 168 to 334

Reference 1

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Observation ab16f7ad-792a-4dc4-8b24-55e6b29bf15f · outbound

This paper cites Fur- thermore, the structure of ViG3D was verified through ablation studies, with specific details provided in the following sections.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Fur- thermore, the structure of ViG3D was verified through ablation studies, with specific details provided in the following sections

Reference 2

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Observation 31b7559e-beb7-478f-9363-efdff48a8b5e · outbound

This paper cites The DSC metrics reflect how accurately the model captures coronary structures.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation The DSC metrics reflect how accurately the model captures coronary structures

Reference 3

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Observation 55e821ce-1a62-4f47-ad51-1704e9569b09 · outbound

This paper cites 3d graph-connectivity constrained network for hepatic vessel segmen- tation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation 3d graph-connectivity constrained network for hepatic vessel segmen- tation,

Reference 4

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Observation 77a8f886-e2a3-437e-ad03-d0824eafd4d1 · outbound

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

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation U-net: Convolutional networks for biomedical image segmentation,

Reference 5

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Observation 201bb55c-618a-49ab-ab61-ff2608d45b6b · outbound

This paper cites A review of deep-learning-based medical image segmentation methods,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation A review of deep-learning-based medical image segmentation methods,

Reference 6

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Observation d739a712-bcba-45cc-8ec6-04781fff53ad · outbound

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

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation nnu-net: a self-configuring method for deep learning-based biomedical image segmentation,

Reference 7

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ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Unresolved cited work

Reference 9

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ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Unresolved cited work

Reference 10

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Observation 4e8b864e-0550-466d-93e3-6f45d1724a35 · outbound

This paper cites Cooper, J.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Cooper, J

Reference 11

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Observation 40321012-d856-4e43-bd80-f32f772e8877 · outbound

This paper cites ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation

Reference 12

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This paper cites Computed tomographic angiography in coronary artery disease,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Computed tomographic angiography in coronary artery disease,

Reference 13

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This paper cites Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with trans- former,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with trans- former,

Reference 14

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Observation 4c437d07-f012-4f3c-aa88-f0689c4e44b4 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Unetr: Transformers for 3d medical image segmentation,

Reference 15

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This paper cites In CNN-based networks, deeper architectures.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation In CNN-based networks, deeper architectures

Reference 16

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Observation da6bd459-b575-4dbf-bac7-2c6d001789aa · outbound

This paper cites The attention mechanism [19] was introduced for more effective aggregation of contextual information.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation The attention mechanism [19] was introduced for more effective aggregation of contextual information

Reference 17

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Observation bae70592-c7eb-4f84-bf12-242eb989999d · outbound

This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 18

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This paper cites Segment anything model for medical image segmentation: Current applications and future directions,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Segment anything model for medical image segmentation: Current applications and future directions,

Reference 20

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This paper cites An energy matching vessel segmentation framework in 3-d medical images,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation An energy matching vessel segmentation framework in 3-d medical images,

Reference 21

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This paper cites Improved topological preservation in 3d axon segmentation and centerline detec- tion using geometric assessment-driven topological smoothing (gats),.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Improved topological preservation in 3d axon segmentation and centerline detec- tion using geometric assessment-driven topological smoothing (gats),

Reference 22

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This paper cites Coronary artery centerline extraction in cardiac ct angiography using a cnn-based orientation classifier,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Coronary artery centerline extraction in cardiac ct angiography using a cnn-based orientation classifier,

Reference 23

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This paper cites 3d u-net: learning dense volumetric segmentation from sparse annotation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation 3d u-net: learning dense volumetric segmentation from sparse annotation,

Reference 24

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This paper cites STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training

Reference 25

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This paper cites Unet++: Redesigning skip connections to exploit multiscale features in image segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation,

Reference 26

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This paper cites Adaptive context selection for polyp segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Adaptive context selection for polyp segmentation,

Reference 27

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This paper cites An improved u-shape neural network for soft exudate segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation An improved u-shape neural network for soft exudate segmentation,

Reference 28

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Observation f5c5a34e-5450-43ca-ad52-1e6006c03421 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 29

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This paper cites Medical transformer: Gated axial-attention for medical image segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Medical transformer: Gated axial-attention for medical image segmentation,

Reference 30

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This paper cites Exfuse: Enhancing feature fusion for semantic segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Exfuse: Enhancing feature fusion for semantic segmentation,

Reference 31

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Observation 163cc4c7-9dce-4289-885f-3a71001c85ff · outbound

This paper cites Ori- net: Orientation-guided neural network for automated coronary arteries segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Ori- net: Orientation-guided neural network for automated coronary arteries segmentation,

Reference 32

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Observation 800cdbf3-4e4e-411c-a34c-2251fbacccd0 · outbound

This paper cites Deep distance transform for tubular structure segmentation in ct scans,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Deep distance transform for tubular structure segmentation in ct scans,

Reference 33

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This paper cites Cs2-net: Deep learning segmentation of curvilinear structures in medical imaging,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Cs2-net: Deep learning segmentation of curvilinear structures in medical imaging,

Reference 34

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Observation e9ed67e6-528a-4437-8f6a-554b4006d7bb · outbound

This paper cites Vision gnn: An image is worth graph of nodes,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Vision gnn: An image is worth graph of nodes,

Reference 35

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

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Graph-based region and boundary aggregation for biomedical image segmentation,

Reference 36

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

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation A joint 3d unet-graph neural network-based method for airway segmen- tation from chest cts,

Reference 37

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This paper cites Graph convolution based cross-network multiscale feature fusion for deep vessel segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Graph convolution based cross-network multiscale feature fusion for deep vessel segmentation,

Reference 38

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This paper cites Imagecas: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Imagecas: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images,

Reference 39

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ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Unresolved cited work

Reference 40

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This paper cites Feature fusion for segmentation and classification of skin lesions,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Feature fusion for segmentation and classification of skin lesions,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:08:27.062924Z

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This paper cites Scs-net: A scale and context sensitive network for retinal vessel segmentation,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Scs-net: A scale and context sensitive network for retinal vessel segmentation,

Reference 42

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Observation 9cceeab6-7fb0-4679-8548-b9ce286aab60 · outbound

This paper cites Vigu: Vi- sion gnn u-net for fast mri,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Vigu: Vi- sion gnn u-net for fast mri,

Reference 43

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Observation 4b6ae6c0-a12d-43fc-8aec-59d6814caef9 · outbound

This paper cites Deepgcns: Can gcns go as deep as cnns?.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Deepgcns: Can gcns go as deep as cnns?

Reference 44

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This paper cites Gaussian Error Linear Units (GELUs).

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Gaussian Error Linear Units (GELUs)

Reference 45

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This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 46

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This paper cites Automated segmen- tation of normal and diseased coronary arteries–the asoca challenge,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Automated segmen- tation of normal and diseased coronary arteries–the asoca challenge,

Reference 47

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Observation a9cc03b9-2744-409f-a6c7-53286be5e4b5 · outbound

This paper cites Deeply-supervised nets,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Deeply-supervised nets,

Reference 48

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This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 49

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This paper cites Innovations in cardiac computed tomography: Imaging in coronary artery disease,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Innovations in cardiac computed tomography: Imaging in coronary artery disease,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:08:26.706867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c7e9260-a6ff-4a48-b8d5-752b7d8f19cf · outbound

This paper cites Non-invasive imaging of the coronary arteries,.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Non-invasive imaging of the coronary arteries,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:08:26.642113Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e9e30258-c5ba-47a0-aec9-946e9a188bbe · outbound

This paper cites Fractal analysis of the vascular tree in the human retina.

ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation Fractal analysis of the vascular tree in the human retina

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:08:26.630690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 40321012-d856-4e43-bd80-f32f772e8877 · inbound