A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD | Paper Citation Record

Observation 6944d985-ee47-45f5-99de-ec1876565550 · outbound

This paper cites As reported by global initiative for chronic obstructive lung disease (GOLD), CT imaging plays an increasingly important role in diagnosis and evaluation of COPD patients [2].

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD As reported by global initiative for chronic obstructive lung disease (GOLD), CT imaging plays an increasingly important role in diagnosis and evaluation of COPD patients [2]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:56.052301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 02588e87-4fee-4d76-9f97-ff08812cf27f · outbound

This paper cites deep learning methods in vessel segmentation In traditional methods, intensity thresholding is the most common method for pulmonary vessel segmentation in CT images [22].

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD deep learning methods in vessel segmentation In traditional methods, intensity thresholding is the most common method for pulmonary vessel segmentation in CT images [22]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:56.029293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 17f7529a-99b5-4bf2-a4c1-96c96b64fd1d · outbound

This paper cites x, y, z, label.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD x, y, z, label

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:56.004449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8d97be7-e2d7-4c2a-b8bd-ac9bef3ae398 · outbound

This paper cites U -shaped.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD U -shaped

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.980205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 57546180-a3b9-41ce-9e6b-7022fd950f1a · outbound

This paper cites an unresolved cited work.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:05:55.954724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a01563de-0d4d-41e7-9ceb-1aa71a295a2f · outbound

This paper cites There are no statistical differences in metric of number of segments, number of endpoints, number of branchpoints, and R (0-1) radius bin across any GOLD grade comparisons.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD There are no statistical differences in metric of number of segments, number of endpoints, number of branchpoints, and R (0-1) radius bin across any GOLD grade comparisons

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.927869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6774bc93-b854-4c81-a4e4-5d610a121752 · outbound

This paper cites The proposed method focuses on capturing the intricacies of smaller vessels.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD The proposed method focuses on capturing the intricacies of smaller vessels

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.901517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 77c7336f-6658-4c83-a27c-ee55c9eda98f · outbound

This paper cites an unresolved cited work.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:05:55.876438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 686bffb9-8450-4b10-ac42-53e9ea229443 · outbound

This paper cites COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.853508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23997ab5-8263-436c-bab3-b2b18c39b5db · outbound

This paper cites Global initiative for chronic obstructive lung disease 2023 report: GOLD executive summary,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Global initiative for chronic obstructive lung disease 2023 report: GOLD executive summary,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.821514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b0df15b8-f0e6-4f54-a7b6-19cd0fb05782 · outbound

This paper cites The Challenges of Spirometric Diagnosis of COPD,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD The Challenges of Spirometric Diagnosis of COPD,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.801922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 045aa430-0f19-424c-840d-d8f5d72a9981 · outbound

This paper cites Recent advances in chronic obstructive pulmonary disease pathogenesis: from disease mechanisms to precision medicine,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Recent advances in chronic obstructive pulmonary disease pathogenesis: from disease mechanisms to precision medicine,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.783022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2cefe2f1-f4eb-4083-9705-ba62e515c503 · outbound

This paper cites A vision transformer for emphysema classification using CT images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD A vision transformer for emphysema classification using CT images,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.764590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b19bc95-43f3-4dd1-b1ee-b191177dd465 · outbound

This paper cites New frontiers in the treatment of comorbid cardiovascular disease in chronic obstructive pulmonary disease,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD New frontiers in the treatment of comorbid cardiovascular disease in chronic obstructive pulmonary disease,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.745167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fc94aa38-a459-4a71-a649-a0acf6ad81d1 · outbound

This paper cites COPD and cardiovascular disease,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD COPD and cardiovascular disease,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.722661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 581f5e4f-715f-41e3-9f1f-7fe0ee829aa5 · outbound

This paper cites Association between systemic and pulmonary vascular dysfunction in COPD,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Association between systemic and pulmonary vascular dysfunction in COPD,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.701849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 584dd045-677b-414c-b6d5-c11b6881f08e · outbound

This paper cites The CT pulmonary vascular parameters and disease severity in COPD patients on acute exacerbation: a correlation analysis,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD The CT pulmonary vascular parameters and disease severity in COPD patients on acute exacerbation: a correlation analysis,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.677824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 83fb2b85-7a4e-4178-a1d1-e92ad1fd7ac8 · outbound

This paper cites Interactive image segmentation via backpropagating refinement scheme,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Interactive image segmentation via backpropagating refinement scheme,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.659381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9a14a0df-76ae-40a4-857a-ff1d45c234fd · outbound

This paper cites Multi -task attention-based semi -supervised learning for medical image segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Multi -task attention-based semi -supervised learning for medical image segmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.632380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c2920157-f50a-40a6-8687-ecef3fce933f · outbound

This paper cites Naviairway: a bronchiole-sensitive deep learning -based airway segmentation pipeline for planning of navigation bronchoscopy,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Naviairway: a bronchiole-sensitive deep learning -based airway segmentation pipeline for planning of navigation bronchoscopy,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.599576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation be7d8d03-5f00-46bf-9701-4eec74142c5f · outbound

This paper cites SCANet: A Unified Semi -supervised Learning Framework for Vessel Segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD SCANet: A Unified Semi -supervised Learning Framework for Vessel Segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.580774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f76790ce-d8cd-4445-947f-e3dc7284575e · outbound

This paper cites A multi -scale interactive U -Net for pulmonary vessel segmentation method based on transfer learning,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD A multi -scale interactive U -Net for pulmonary vessel segmentation method based on transfer learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.551882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 765ce26d-d40f-4090-bfa4-4e34b535ef58 · outbound

This paper cites Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.526401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 60ac489b-7748-4c7d-a967-eb838f208515 · outbound

This paper cites Automated vessel segmentation in lung CT and CTA images via deep neural networks,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Automated vessel segmentation in lung CT and CTA images via deep neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.492901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 86cbb329-f2f5-4cfe-ac0d-1c8f39c252da · outbound

This paper cites nnFormer: Interleaved Transformer for Volumetric Segmentation.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD nnFormer: Interleaved Transformer for Volumetric Segmentation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:54.530715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ccadadf-593e-4401-8dc5-62c0bd29ca4c · outbound

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

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:54.537804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b959216c-2c40-4883-91ec-c56ee1c695be · outbound

This paper cites Ds-transunet: Dual swin transformer u-net for medical image segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Ds-transunet: Dual swin transformer u-net for medical image segmentation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.462147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 78efa3a4-ca15-4738-900e-5ac75e41eb19 · outbound

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

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.443356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 20b6af51-71b9-4d05-9988-a199061ee719 · outbound

This paper cites SAM3D: Segment Anything Model in Volumetric Medical Images.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD SAM3D: Segment Anything Model in Volumetric Medical Images

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:54.555199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d25f751d-36fd-4c74-8726-b5d60d7938b5 · outbound

This paper cites Determination of vessel cross -sectional area by thresholding in Radon space,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Determination of vessel cross -sectional area by thresholding in Radon space,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.421888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e3423d1-f596-4c3f-ab86-75b771102566 · outbound

This paper cites Region growing: a new approach,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Region growing: a new approach,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.399839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81f0afa3-c155-4e0e-b808-402946398a39 · outbound

This paper cites Segmentation of pulmonary vascular tree by incorporating vessel enhancement filter and variational region -growing,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Segmentation of pulmonary vascular tree by incorporating vessel enhancement filter and variational region -growing,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.379771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4db4749a-69d1-4135-aea8-8275d8968e83 · outbound

This paper cites Edge detection techniques-an overview,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Edge detection techniques-an overview,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.362151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 506cc7cb-4dcc-48d2-a98e-0d0e30b7e741 · outbound

This paper cites An efficient retinal blood vessel segmentation using morphological operations,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD An efficient retinal blood vessel segmentation using morphological operations,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.343593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06db135b-3d69-4e97-9b93-9e1f498b5a97 · outbound

This paper cites Fuzzy pulmonary vessel segmentation in contrast enhanced CT data,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Fuzzy pulmonary vessel segmentation in contrast enhanced CT data,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.318560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b40f3619-0116-4a05-ba6b-5e353524ee53 · outbound

This paper cites Regulated morphology approach to fuzzy shape analysis with application to blood vessel extraction in thoracic CT scans,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Regulated morphology approach to fuzzy shape analysis with application to blood vessel extraction in thoracic CT scans,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.292954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b82289b8-3c76-458a-b495-19d3629c05e8 · outbound

This paper cites Pulmonary vessel segmentation based on orthogonal fused u-net++ of chest CT images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Pulmonary vessel segmentation based on orthogonal fused u-net++ of chest CT images,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.273343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f0a910a8-2bd6-45d9-868b-e4762bc14679 · outbound

This paper cites NCCT -CECT image synthesizers and their application to pulmonary vessel segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD NCCT -CECT image synthesizers and their application to pulmonary vessel segmentation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.249095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6a0d00ae-9be9-4c41-b1eb-a62d30eacb87 · outbound

This paper cites Transformer-based 3D U -Net for pulmonary vessel segmentation and artery -vein separation from CT images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Transformer-based 3D U -Net for pulmonary vessel segmentation and artery -vein separation from CT images,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.229272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cfb7ae95-05a4-4578-94aa-6d802de8f65c · outbound

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

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD U -net: Convolutional networks for biomedical image segmentation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.206737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c3586939-7fb1-406a-9329-577b09118357 · outbound

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

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD V -net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:54.625522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c6692b-06ec-44a9-a39f-d16cf41eab57 · outbound

This paper cites 3D U-Net: learning dense volumetric segmentation from sparse annotation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD 3D U-Net: learning dense volumetric segmentation from sparse annotation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.173772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5cf1be99-df89-4e75-8567-26db1f6c679b · outbound

This paper cites Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery -vein separation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery -vein separation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.155103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 10c40075-14bc-4b21-b3e6-b11558ce0941 · outbound

This paper cites Learning tubule -sensitive cnns for pulmonary airway and artery -vein segmentation in ct,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Learning tubule -sensitive cnns for pulmonary airway and artery -vein segmentation in ct,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.136076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6558c4b1-59d4-4ee6-b682-01bd953546a2 · outbound

This paper cites Segmentation and suppression of pulmonary vessels in low‐ dose chest CT scans,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Segmentation and suppression of pulmonary vessels in low‐ dose chest CT scans,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.107960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b5b19b8d-1c08-4551-8f2e-92816c7b01e1 · outbound

This paper cites A Pulmonary Vascular Extraction Algorithm from Chest CT/CTA Images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD A Pulmonary Vascular Extraction Algorithm from Chest CT/CTA Images,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.086318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2104ab35-d5b9-4331-89a8-496561e3af35 · outbound

This paper cites Semi -supervised multiple evidence fusion for brain tumor segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Semi -supervised multiple evidence fusion for brain tumor segmentation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.064356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4e20411d-65b7-4dc3-8321-83fe049b9a46 · outbound

This paper cites Chestx -ray8: Hospital-scale chest x -ray database and benchmarks on weakly -supervised classification and localization of common thorax diseases,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Chestx -ray8: Hospital-scale chest x -ray database and benchmarks on weakly -supervised classification and localization of common thorax diseases,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.045498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93c682c1-03b1-4323-92c4-02b9891dae42 · outbound

This paper cites St++: Make self-training work better for semi - supervised semantic segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD St++: Make self-training work better for semi - supervised semantic segmentation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:55.001326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3c2c1525-978f-4a0e-bf49-01be14ade843 · outbound

This paper cites CE-NC-VesselSegNet: Supervised by contrast-enhanced CT images but utilized to segment pulmonary vessels from non-contrast-enhanced CT images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD CE-NC-VesselSegNet: Supervised by contrast-enhanced CT images but utilized to segment pulmonary vessels from non-contrast-enhanced CT images,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.982008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1c7c0f56-c8cb-4154-b122-4817e0c6c98d · outbound

This paper cites Dense biased networks with deep priori anatomy and hard region adaptation: Semi - supervised learning for fine renal artery segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Dense biased networks with deep priori anatomy and hard region adaptation: Semi - supervised learning for fine renal artery segmentation,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.957149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 38e78688-ae24-4406-9875-8f4e3bc74b82 · outbound

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

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Unetr: Transformers for 3d medical image segmentation,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T18:05:54.686369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5476591-ba74-442a-b77d-0ae17f7cda14 · outbound

This paper cites A fully automatic segmentation pipeline of pulmonary lobes before and after lobectomy from computed tomography images,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD A fully automatic segmentation pipeline of pulmonary lobes before and after lobectomy from computed tomography images,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.918770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b492362-4563-43af-b517-9d6854439e51 · outbound

This paper cites Open -source analysis and visualization of segmented vasculature datasets with VesselVio,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Open -source analysis and visualization of segmented vasculature datasets with VesselVio,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.892831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28cfc714-ad8f-420b-b6e8-72a1fdc9e95a · outbound

This paper cites Self-supervised pre-training of swin transformers for 3d medical image analysis,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Self-supervised pre-training of swin transformers for 3d medical image analysis,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.874738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b978da89-225a-4b99-af69-170502b0c2a9 · outbound

This paper cites Self -supervised learning for few- shot medical image segmentation,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Self -supervised learning for few- shot medical image segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.858140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 99a342ba-2098-4981-8e0b-8c355b5b3eb7 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Diffusion models: A comprehensive survey of methods and applications,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.840013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4a11e27d-b7d3-4fe2-8672-6449b72feec5 · outbound

This paper cites Diffusion models in vision: A survey,.

A Self-training Framework for Semi-supervised Pulmonary Vessel Segmentation and Its Application in COPD Diffusion models in vision: A survey,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:05:54.814059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers