Paper Citation Record · LEDGER

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.22222.

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

pith.paper-citation-record.v1
2506.22222 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:14:09.980166Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy22
unresolved2
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 800e1b8d-1abc-47f8-85d8-0442eceaaa42 · outbound

This paper cites ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T22:14:10.354221Z

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 2cf9b992-4b32-4472-80fd-cfcd34b224b2 · outbound

This paper cites The International Registry of Acute Aortic Dissection (IRAD)New Insights Into an Old Disease.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections The International Registry of Acute Aortic Dissection (IRAD)New Insights Into an Old Disease

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T22:14:14.920310Z

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 c07eb45f-e5f5-49fb-8373-9724a9fdd707 · outbound

This paper cites Management of acute aortic dissection.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Management of acute aortic dissection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:14.762968Z

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 6a5f56c1-ae83-4401-a8ab-3c085628e036 · outbound

This paper cites Standardized Protocol to Analyze Computed Tomography Imaging of Type B Aortic Dissections.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Standardized Protocol to Analyze Computed Tomography Imaging of Type B Aortic Dissections

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:14.596636Z

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 637f2919-ab91-4b03-aaf4-b2fe5643839f · outbound

This paper cites Importance of false lumen thrombosis in type B aortic dissection prognosis.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Importance of false lumen thrombosis in type B aortic dissection prognosis

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:14.439148Z

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 9a5ffdf3-6eb3-4c47-80ab-ada11eed8a99 · outbound

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

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections U-net: Convolutional networks for biomedical image segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:14.242531Z

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 33a0b921-11a2-486e-943b-f80d1a4d176b · outbound

This paper cites Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.947816Z

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 04929d40-8fd8-4cfa-ae85-d068ba08effb · outbound

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

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.756366Z

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 ed626cd3-c905-4373-bbcc-714da50ddfed · outbound

This paper cites Using DUCK-Net for polyp image segmentation.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Using DUCK-Net for polyp image segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.603883Z

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 3a9ebc68-cb92-40df-819e-60849e90cf3e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale; 2021.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale; 2021

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.452187Z

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 4302e958-0218-4ede-a0cb-276acf64ca63 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation; 2021.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation; 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.272217Z

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 a21f32a2-fc19-4680-8dd9-5259f9d3d5aa · outbound

This paper cites Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation; 2021.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation; 2021

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:13.111614Z

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 8de7c7d6-761f-493c-84d3-587fa3657de9 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces; 2022.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Efficiently Modeling Long Sequences with Structured State Spaces; 2022

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.947298Z

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 75af6011-6c98-41d2-8fac-1391fd350688 · outbound

This paper cites SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation; 2024.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation; 2024

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.840676Z

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 b0240037-441e-4c4c-81f2-ac51805a2be3 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation; 2024.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation; 2024

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.698252Z

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 c44ab1de-0904-4d16-9afc-359161b31198 · outbound

This paper cites Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.483555Z

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 1e1a44f1-5716-48c9-903f-53fdc866513c · outbound

This paper cites Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.336749Z

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 95215bee-2304-4b3c-8d89-845cd7091a66 · outbound

This paper cites an unresolved cited work.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T22:14:14.115647Z

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 5adf80fa-b536-4adc-a3a2-edaec7d4d765 · outbound

This paper cites Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:12.109557Z

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 3979721e-1e09-4154-99eb-b41ad3e39603 · outbound

This paper cites ADSeg: A flap-attention-based deep learning approach for aortic dissection segmentation.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections ADSeg: A flap-attention-based deep learning approach for aortic dissection segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:11.914926Z

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 c3b073f8-63da-4dc2-9860-84fe92d1f84c · outbound

This paper cites CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:11.670708Z

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 dd6f5fe1-488f-43ab-9e5c-92e9b61d9017 · outbound

This paper cites 3D U-Net: Learning Dense V olumetric Segmentation from Sparse Annotation; 2016.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections 3D U-Net: Learning Dense V olumetric Segmentation from Sparse Annotation; 2016

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:11.377563Z

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 b73cd225-2561-4206-b3cf-659c05f93f88 · outbound

This paper cites Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images; 2022.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images; 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:11.111659Z

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 4233ad59-6ef5-4877-a328-aafb38c3ac31 · outbound

This paper cites Densely Connected Convolutional Networks; 2018.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Densely Connected Convolutional Networks; 2018

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:10.824101Z

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 ca8a4cb3-055f-4a30-906e-b9cb42ac9fb0 · outbound

This paper cites In: Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections In: Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations

Reference 25

Resolution: malformed identifier; no resolver link, observed 2026-08-06T22:14:09.713265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad9f35db-71bc-4eb8-9cc0-0b1a04e31462 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library; 2019.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections PyTorch: An Imperative Style, High-Performance Deep Learning Library; 2019

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:14:10.604587Z

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 d069b9b7-e041-45f4-ac5c-83f42b29be93 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Advanced Deep Learning Techniques for Automated Segmentation of Type B Aortic Dissections Adam: A Method for Stochastic Optimization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T22:14:09.980166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.