Paper Citation Record · LEDGER

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation

As of 20 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2412.06530.

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

pith.paper-citation-record.v1
2412.06530 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:35:39.714791Z

measured 23 of 23 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

23 of 23 outbound references displayed

verified exact0
verified fuzzy12
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0aa2a72-4bce-4b64-8cfd-a42bbe5165e3 · outbound

This paper cites Echinococcosis of the liver,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Echinococcosis of the liver,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:40.045261Z

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 6214f6f1-8f7a-4382-a058-0ce1e36cddf4 · outbound

This paper cites Advances in liver echinococcosis: diagnosis and treat- ment,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Advances in liver echinococcosis: diagnosis and treat- ment,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:40.030638Z

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 42b2990d-593b-4448-be54-aa20d22f1250 · outbound

This paper cites A computational approach to edge detection,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation A computational approach to edge detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:40.014865Z

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 4a9bc228-ca4d-400f-8fe9-a75e78ed6f27 · outbound

This paper cites Seeded region growing,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Seeded region growing,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.999911Z

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 1e7fad72-b9e7-4075-b80f-4c6fea862281 · outbound

This paper cites Gradient-based learning applied to document recognition,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Gradient-based learning applied to document recognition,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.636398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d66a956-f8d0-45f4-9d45-de5afdb5d007 · outbound

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

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation U-net: Con- volutional networks for biomedical image segmentation,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.640559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40368681-5d4e-4977-9234-8e9230c218d8 · outbound

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

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.645313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347f26d4-1353-4287-aefe-0a15c33b7754 · outbound

This paper cites Attention is all you need,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Attention is all you need,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.649339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d0246e5-ff59-4456-803e-c99172293296 · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Swin-unet: Unet-like pure transformer for medical image segmentation,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.653298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b269eac9-ecc9-435f-a851-03a76ed95bbe · outbound

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

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation 3d u-net: learning dense volumetric seg- mentation from sparse annotation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.948012Z

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 e1cce901-1003-4a02-8337-2ab5ed9711c7 · outbound

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

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation V-net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.665247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3214970-ebf4-4b7d-ae5a-05066f2a437b · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Unet++: A nested u-net architecture for medical image segmentation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.669782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d3ce085-a253-4890-aa29-9f414e05bdea · outbound

This paper cites Msa2net: Multi-scale adaptive attention-guided network for medical image segmentation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Msa2net: Multi-scale adaptive attention-guided network for medical image segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.899085Z

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 9c3ee0c9-02a4-43d6-9aa2-7437ae5f6ec2 · outbound

This paper cites Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Haar wavelet downsampling: A simple but effective downsampling module for semantic segmentation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.884117Z

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 8b6ac33c-5786-4cbe-bc90-0d9543dd540f · outbound

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

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.682587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0529281b-93ce-44b1-9288-d6d03c7a92f9 · outbound

This paper cites Hepatic echinococcosis: clinical and therapeutic aspects,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Hepatic echinococcosis: clinical and therapeutic aspects,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.868168Z

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 a319a983-e1db-45e6-8f27-2e5c40e5e7b2 · outbound

This paper cites Ege-unet: an efficient group enhanced unet for skin lesion segmentation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Ege-unet: an efficient group enhanced unet for skin lesion segmentation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.854273Z

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 773c8662-d07d-4c32-a2dd-c60edc16c801 · outbound

This paper cites Cbam: Convolutional block attention module,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Cbam: Convolutional block attention module,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.840761Z

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 80f83895-589f-4261-b682-59dd10e41485 · outbound

This paper cites an unresolved cited work.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:35:39.933339Z

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 f22953cc-7116-43cf-bac1-40d8f098f0a2 · outbound

This paper cites An efficient encoder-decoder architecture with top-down attention for speech separation.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation An efficient encoder-decoder architecture with top-down attention for speech separation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.700121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cb66bbe-9133-4ce3-89db-bd2ceb3f896a · outbound

This paper cites Iianet: An intra- and inter-modality attention network for audio-visual speech separation,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Iianet: An intra- and inter-modality attention network for audio-visual speech separation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.826014Z

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 a0f70e9d-1f82-47cc-b18c-67cb0e6f4b6d · outbound

This paper cites Decoupled Weight Decay Regularization.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Decoupled Weight Decay Regularization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T19:35:39.709998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f42868b-c1cc-4f31-bff8-87b5cf86cd17 · outbound

This paper cites Resunet-a: A deep learning framework for semantic segmentation of remotely sensed data,.

HES-UNet: A U-Net for Hepatic Echinococcosis Lesion Segmentation Resunet-a: A deep learning framework for semantic segmentation of remotely sensed data,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:35:39.810610Z

Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.