Paper Citation Record · LEDGER

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation

As of 13 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2501.10615.

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

pith.paper-citation-record.v1
2501.10615 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:06:36.508654Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:06:36.056205Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T19:06:36.770676Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0be6d1d8-ee5c-4953-9910-7f2b48443cf8 · outbound

This paper cites Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T19:06:36.784532Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation beb89261-9bb9-49bc-9729-817e617f0ef1 · outbound

This paper cites Semi-automatic methods in- volve manual lumen boundary and centerline annotation, achieving good performance but are labor-intensive.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Semi-automatic methods in- volve manual lumen boundary and centerline annotation, achieving good performance but are labor-intensive

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.794153Z

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Observation 532fdc14-8ae7-4a12-b67b-77b9ea9dbd18 · outbound

This paper cites We propose a hier- archical LoG module to address these issues and enhance aorta segmentation.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation We propose a hier- archical LoG module to address these issues and enhance aorta segmentation

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T19:06:37.771612Z

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Observation 44e4c982-37c9-46c0-abb2-6ffe156b8199 · outbound

This paper cites Two datasets were used: the first is from [23], and the second is the Aortic Ves- sel Tree (A VT) CTA dataset [24].

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Two datasets were used: the first is from [23], and the second is the Aortic Ves- sel Tree (A VT) CTA dataset [24]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.745382Z

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Observation abd34901-804e-4b45-aba8-c2bd4b554a7d · outbound

This paper cites an unresolved cited work.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T19:06:37.706618Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2844fe05-bcc6-4dce-8498-7011dda73fac · outbound

This paper cites Ethical approval was not required, as confirmed by the licenses attached to the open- access datasets.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Ethical approval was not required, as confirmed by the licenses attached to the open- access datasets

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.682524Z

Source-reported events for the cited work

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Observation 2e2917e2-f4c1-40bc-98d0-53378908e810 · outbound

This paper cites The au- thors would like to thank the anonymous reviewers for their insightful comments.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation The au- thors would like to thank the anonymous reviewers for their insightful comments

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.650187Z

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Observation 22bd59da-335b-4ea5-aff1-4bb62406290c · outbound

This paper cites U-Net: Convolu- tional networks for biomedical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation U-Net: Convolu- tional networks for biomedical image segmentation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.623874Z

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Observation f05f8369-f9ab-4ff4-b74f-14e0f88d21a4 · outbound

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

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation 3D U-Net: Learning dense volumetric segmentation from sparse annotation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.592831Z

Source-reported events for the cited work

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Observation 057116e0-de62-45f1-91c0-52771e0ec67e · outbound

This paper cites Enabling supra- aortic vessels inclusion in statistical shape models of the aorta: A novel non-rigid registration method,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Enabling supra- aortic vessels inclusion in statistical shape models of the aorta: A novel non-rigid registration method,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.568983Z

Source-reported events for the cited work

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Observation c5687d74-7ba1-4f40-a932-da239c5223be · outbound

This paper cites SimVascular: An open source pipeline for cardio- vascular simulation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation SimVascular: An open source pipeline for cardio- vascular simulation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.542527Z

Source-reported events for the cited work

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Observation 33466805-3b58-43fb-a1e4-8c8e0d4fde70 · outbound

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

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Attention U-Net: Learning Where to Look for the Pancreas

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T19:06:36.167403Z

Source-reported events for the cited work

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Observation bd525728-d08c-460d-a5f0-a5902ee51866 · outbound

This paper cites Geometric uncertainty in patient-specific cardiovascu- lar modeling with convolutional dropout networks,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Geometric uncertainty in patient-specific cardiovascu- lar modeling with convolutional dropout networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.520581Z

Source-reported events for the cited work

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Observation cb5ed1ae-8373-4881-b1f7-73605aec92da · outbound

This paper cites Automatic aortic dissection center- line extraction via morphology-guided CRN tracker,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Automatic aortic dissection center- line extraction via morphology-guided CRN tracker,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.482609Z

Source-reported events for the cited work

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Observation 0c4c7362-fa83-4140-b775-a19ce682b3f6 · outbound

This paper cites AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

Reference 15

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Observation 49b98c7d-3e7c-42de-a8fb-45a69599b1ec · outbound

This paper cites A model based method for retinal blood vessel detection,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation A model based method for retinal blood vessel detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.439838Z

Source-reported events for the cited work

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Observation 169eb828-2aea-4a41-baf4-db71566fd58b · outbound

This paper cites Pyramid scene parsing network,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Pyramid scene parsing network,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.411628Z

Source-reported events for the cited work

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Observation 7735d906-0bdb-4bba-b147-6c2b1169c348 · outbound

This paper cites The one hundred layers tiramisu: Fully convolutional DenseNets for semantic segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation The one hundred layers tiramisu: Fully convolutional DenseNets for semantic segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.382608Z

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Observation 224cb269-c091-4659-8cb6-ac579745fd00 · outbound

This paper cites kCBAC- Net: Deeply supervised complete bipartite networks with asymmetric convolutions for medical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation kCBAC- Net: Deeply supervised complete bipartite networks with asymmetric convolutions for medical image segmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.349112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 17f9c650-3166-4589-94ab-eef47b734a47 · outbound

This paper cites UNETR: Transformers for 3D medical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation UNETR: Transformers for 3D medical image segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.302256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8969eb66-1145-492a-8645-7e3ebb9b7608 · outbound

This paper cites UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation

Reference 21

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Source-reported events for the cited work

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Observation 9524cfae-1418-419c-a9ec-687d555943d2 · outbound

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

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Swin UNETR: Swin transformers for semantic segmentation of brain tumors in MRI images,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.273405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c6563544-3175-4e50-b169-b9e08515a22f · outbound

This paper cites ConvFormer: Com- bining CNN and transformer for medical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation ConvFormer: Com- bining CNN and transformer for medical image segmentation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.249607Z

Source-reported events for the cited work

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Observation ff4be268-e904-4604-b74e-9b89bdbc75c1 · outbound

This paper cites Gated- SCNN: Gated shape CNNs for semantic segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Gated- SCNN: Gated shape CNNs for semantic segmentation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.194647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4324aa1f-accd-4063-a1bc-cc40de2be4f0 · outbound

This paper cites Uncertainty quantification using variational inference for biomedical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Uncertainty quantification using variational inference for biomedical image segmentation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.169234Z

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Observation f86d5117-760f-47a1-8d46-84e0311ed75f · outbound

This paper cites Blood vessel segmentation algorithms - review of methods, datasets and evaluation metrics,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Blood vessel segmentation algorithms - review of methods, datasets and evaluation metrics,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.134394Z

Source-reported events for the cited work

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Observation 884c2e10-c1ab-4f4b-81c7-5d814d1308fd · outbound

This paper cites DCU-Net: A de- formable convolutional neural network based on cascade U- Net for retinal vessel segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation DCU-Net: A de- formable convolutional neural network based on cascade U- Net for retinal vessel segmentation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.104198Z

Source-reported events for the cited work

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Observation ac519db7-e808-4bb5-852c-e706e607a6f7 · outbound

This paper cites Automatic liver vessel segmentation using 3D region growing and hybrid active contour model,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Automatic liver vessel segmentation using 3D region growing and hybrid active contour model,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.078494Z

Source-reported events for the cited work

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Observation f628ba86-9d3c-45ba-8e33-c352b79d3913 · outbound

This paper cites Explanation and use of uncertainty quantified by Bayesian neural network clas- sifiers for breast histopathology images,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Explanation and use of uncertainty quantified by Bayesian neural network clas- sifiers for breast histopathology images,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.052678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55ef5057-b98f-47e0-98fb-00a2d736fa66 · outbound

This paper cites The vascular model repository: A public resource of medical imaging data and blood flow simulation results,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation The vascular model repository: A public resource of medical imaging data and blood flow simulation results,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:37.026426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 54cb9ec3-96c1-42ec-8fa8-d2aed8851306 · outbound

This paper cites A VT: Mul- ticenter aortic vessel tree CTA dataset collection with ground truth segmentation masks,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation A VT: Mul- ticenter aortic vessel tree CTA dataset collection with ground truth segmentation masks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:36.971558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9fe85eed-31eb-492d-b794-bcfddce41522 · outbound

This paper cites Feature pyramid networks for object detection,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation Feature pyramid networks for object detection,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:36.939080Z

Source-reported events for the cited work

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Observation 96b4340f-1810-4e4c-9cec-9751be4dc823 · outbound

This paper cites nnU-Net: A self-configuring method for deep learning-based biomedical image segmentation,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation nnU-Net: A self-configuring method for deep learning-based biomedical image segmentation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:36.886108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b6a0b22-1456-4af7-8163-990b78a34d95 · outbound

This paper cites MISSFormer: An Effective Medical Image Segmentation Transformer.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation MISSFormer: An Effective Medical Image Segmentation Transformer

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T19:06:36.466990Z

Source-reported events for the cited work

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Observation 715f4e1c-d93c-48d3-9ac8-70755a64bea3 · outbound

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

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T19:06:36.480494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 447a3f3f-79c7-41eb-bb68-84af2f3f8728 · outbound

This paper cites An image-based modeling frame- work for patient-specific computational hemodynamics,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation An image-based modeling frame- work for patient-specific computational hemodynamics,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:36.849665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cf9b6c18-e23c-49be-b816-2c9a6fdfaeb8 · outbound

This paper cites A tensorial approach to computational continuum mechanics using object- oriented techniques,.

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation A tensorial approach to computational continuum mechanics using object- oriented techniques,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:06:36.827775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 0be6d1d8-ee5c-4953-9910-7f2b48443cf8 · inbound