Pith. sign in

Paper Citation Record · LEDGER

Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation

As of 14 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 2026-08-13T06:32:02.005865+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

  • verified exact0
  • verified fuzzy29
  • unresolved6
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.056205Z digest=sha256:20d83eca9ac5c9b1681af9f508e85d400ecac07555c9c44be67d5fb66174ae9d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.073702Z digest=sha256:a9c3c1e6b18f445c04e1c919b120db5eebcef6518ec153825307f894b34c7977

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.085305Z digest=sha256:edda829ba804754525764e7a3d3ac0009ed95d6f9c25f9e308087932cdbf9c10

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.095635Z digest=sha256:bd50f6178d5055ffc1979e6e1e07b7abd4f9a75af9c8271bb58bba6b6b44c38f

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.101983Z digest=sha256:f543cd2a55a7a8fa83d10d1b9e0b25b3abb0fcbb7c2fcc96152ddf8ce59ee27c

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.106701Z digest=sha256:8173037b1e50be77cb93652c22e95421dad9b8cd2e57cc1e66b74385fe640de2

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.111928Z digest=sha256:f9b4e425ad8a0fe92248ecb4db8fc984e0785edd06720cf849b1a3d4c1032e2c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.120168Z digest=sha256:ec594a6c04bbc37c031edeae226d202b5d73b9bb73722fd8358c802a90557317

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.129046Z digest=sha256:d9da8395b5940450bdcf6ed13cfe1aac06eb602067db1f4a0729313a613bae7e

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.148384Z digest=sha256:e500d9b247b7dc0b244245ae1741eeb10aa138c75959dc310086d0300910b851

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.154079Z digest=sha256:de5a45e9339b6c7033a4f3079d5d4e4409a780513aed02fd91b5314691844bd4

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:06:36.167403Z digest=sha256:456ea6f59f6be1b881971b36f60f053f519aef6b69ba00d52e541e025f4f6288

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.178841Z digest=sha256:1e831dd75d01fd9c50294f0782d4edb503584f0b7935f11f5fcc63edad5bdcf4

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.185508Z digest=sha256:c12c7c9c60a3436f5f312327210093e966bb80ae99afdb1d015ca670943d4918

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

Resolution
unresolved
no resolver link, observed 2026-08-10T19:06:36.199330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:06:36.199330Z digest=sha256:791ba385248fba8d09014a428d5a2c2e4d5a94c6afe921a2317d11d3285bd47a

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.208512Z digest=sha256:17ba54d003c0a1780a22ade68a29e4da516e9a313d98b77cdcf1a8e25b6011ca

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.223439Z digest=sha256:a4abe4f329879066ac053c4b75a3e62501ad444ff4660cb25a8e919aa4dcfc97

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.239179Z digest=sha256:5d1d18cc0e05b0bfaa0b17a77dff9c5385881539ed0eefb29df5534bc14a8c97

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.257459Z digest=sha256:65ed5e4d77712422c2ec0a8bf459443e66a67898b9a59eccca73215afff24654

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.266378Z digest=sha256:9e05cd76f7ca7c2f07f3c8c82c62c782f2ba30c4eab2bd8ae1650007b30837da

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

Resolution
unresolved
no resolver link, observed 2026-08-10T19:06:36.275326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:06:36.275326Z digest=sha256:570dff6c4774f15bf78f1bb4f10889ccb656a3dc8a6cc629ac9bf1dc9b1dd807

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.282956Z digest=sha256:cc4602f4bb83ca2f5388b7e12fe96e65759c8e5a3c8823bd7107d1b9563089af

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.288693Z digest=sha256:8f6da3becab190a517644c74474e5e9c0363b58c45801182c6eb3bc676a8fe72

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.342321Z digest=sha256:2a0f1a80171de3d2b284ee1fc4126d9d200b84f2da06014cc605af65259a8b85

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.356287Z digest=sha256:baf7c8880fb1e0b96b464113979ac578207fa860e284ca43eabc12350f0cd8d2

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.364244Z digest=sha256:5ff93940235b697f4a36584db01e86dc180362ec8f321968b32bcdd6604b8fef

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.373199Z digest=sha256:7f494ca93cac1cc8878a4036c0859789fd8862e83273fa984fe15e101a40341a

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.383358Z digest=sha256:64d671d613399ea9705e3cc5753e3a855b13b5f2826fdaec9eb141e96ad18f0d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.417309Z digest=sha256:30721d55d3fc6e590f1886016ec5df7c587df3050d9d626c23f116b18c4e042a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.426130Z digest=sha256:10eb4b3414224abdd3373477caccf8516a759f30c37efc10d6bcfa2fedbcc36f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.433213Z digest=sha256:ea38e3072c9da4e932ae6cc585fe1fc28b400abf167bdecf74480be33ef3bceb

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

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.442396Z digest=sha256:5a5a1adbbb14a41ce98232e8364d7c5b68f792edba3997d9b72bfabffcdd3d2c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.459623Z digest=sha256:a4de8a073b199bf2815e937894e47fb564235a6ee7d335e7227192325908a0bb

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:06:36.466990Z digest=sha256:dfc6c085bcd29a30f27378803f36b46b8dc7a256f5bd5c71ab9291e94b5ae3e3

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.

source=pdf_text observed=2026-08-10T19:06:36.480494Z digest=sha256:0c60a4e192d4a961e843e18c9fa8d1a1d8011e4fc03ebeb3447c33472f8b1dd4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.501184Z digest=sha256:ab016acfdc869385e088f420dc37418c45e0db5d1f9f86168bb985c4f51c217e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.508654Z digest=sha256:bf4eed5b51d3409be78d539731d5416d9632620a39cc6897a7c3cf8d27a974f6

Pith citing papers

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

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T19:06:36.056205Z digest=sha256:20d83eca9ac5c9b1681af9f508e85d400ecac07555c9c44be67d5fb66174ae9d