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Paper Citation Record · LEDGER

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2507.07126.

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

pith.paper-citation-record.v1
2507.07126 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:10:57.687124Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy19
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56118361-3a12-4317-a1f1-7f07a36b9385 · outbound

This paper cites Cancers14(3), 637 (2022).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Cancers14(3), 637 (2022)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.386777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.172663Z digest=sha256:d8ee574eea92262c99f49c4b27af2d4227f5672c27429a896dd08917f41e173c

Observation 91e7149d-30ea-4991-99e8-ec3103e9ec24 · outbound

This paper cites Oncotarget 6(1), 570 (2014).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Oncotarget 6(1), 570 (2014)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.339338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.232844Z digest=sha256:37da8a1e54fd761d7b667e08d3fc1f3f8e71321d625b641b1b2e31173f2deff6

Observation 0e90586d-4f65-4546-9bab-91eefa55bee6 · outbound

This paper cites Pattern Recognition145, 109881 (2024).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Pattern Recognition145, 109881 (2024)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.303812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.288296Z digest=sha256:c8b0b7e0489e0215e66f7998546fa9c57ff0fcad479a0c86025a5341ae44b216

Observation fe5a8b04-7a27-4704-867e-bf3190118cd6 · outbound

This paper cites International journal of clinical oncology11, 286–296 (2006).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation International journal of clinical oncology11, 286–296 (2006)

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.267340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.354514Z digest=sha256:6612b3f1da6558b965b3d5aee3dbd05704005b7e94185db84cf193c1be2195ce

Observation beea29e1-cce0-400f-aca8-6b67ab59fdfc · outbound

This paper cites Nature Communications15(1), 9613 (2024).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Nature Communications15(1), 9613 (2024)

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.204623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.389150Z digest=sha256:86abf7c9f819a30d96cb3f1f90bfaf4877d663a0f3be48bb05f105d7464d8eb5

Observation e15adb87-3ddd-4324-8487-a3654a300aec · outbound

This paper cites Data9(1), 601 (2022).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Data9(1), 601 (2022)

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.167819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.425474Z digest=sha256:bcda9435c0d24211ee8ba3bd550d020e80e0d011164b1f287a7924907b49a88d

Observation 08057e17-18f3-427d-8a1f-7eac5f43e39a · outbound

This paper cites Radiology266(2), 388–405 (2013).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Radiology266(2), 388–405 (2013)

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.119807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.506780Z digest=sha256:10fe21acf306644b59104ac80e67ebc8ecae53a49e189a73dc43a0cd23971208

Observation 343ab97b-7ccb-4eb1-8e05-333e039c3cf2 · outbound

This paper cites The Lancet Digital Health6(2), e114–e125 (2024) 10 X.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation The Lancet Digital Health6(2), e114–e125 (2024) 10 X

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:11:00.074751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.563693Z digest=sha256:11f9f1d041e3aae64ae7724be2625f7a9dcacfce28823c326c9937d70b266fa2

Observation 67fb56c7-685e-444f-846e-67c575c8da02 · outbound

This paper cites In: International MICCAI brainlesion workshop.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: International MICCAI brainlesion workshop

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:56.601400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:56.601400Z digest=sha256:60c2dfa793fb56106eb9ccc6c1bbca0c4c15a14fee6926d42924fb4f2a22316a

Observation c03f583e-83fd-4c33-b9c2-5d1aeb8be8ce · outbound

This paper cites In: Proceedings of the IEEE/CVF winter conference on applications of computer vi- sion.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: Proceedings of the IEEE/CVF winter conference on applications of computer vi- sion

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:56.639002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:56.639002Z digest=sha256:81cc69ffa9888b1387475490a51d1a4715f694ae528f7d0e292b9a891a4a50c5

Observation 948f3d2e-0036-48da-aa36-c37f8ef1dbf2 · outbound

This paper cites STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:56.711580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:56.711580Z digest=sha256:b71a2bfccf94829cd02060256b977512b2219780c99407368ab167f088298839

Observation 23478a8e-0e45-4556-bb57-bd039625f4d9 · outbound

This paper cites Nature methods 18(2), 203–211 (2021).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Nature methods 18(2), 203–211 (2021)

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:56.771937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:56.771937Z digest=sha256:24adecc2e59b7475d4e728089ae43dae49c5ca60e474d9c33b53035403a882d3

Observation 555f35d7-0c03-4663-8f34-810a18ea6d19 · outbound

This paper cites Journal of clinical oncology28(20), 3271–3277 (2010).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Journal of clinical oncology28(20), 3271–3277 (2010)

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.957638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.843530Z digest=sha256:38457dc9a6a5aa3b4fd9b228b74a0e23411e4d1b3575839f1172358b52b9481a

Observation 52583f37-fb4f-4527-8c9d-fb0f458c2774 · outbound

This paper cites 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:56.886563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:56.886563Z digest=sha256:27e964c96f230c6578b8b236168a73a166342a3c792040294ae17e1ed2a8de37

Observation af92425d-1d11-4ee0-8a27-ff76613c1e31 · outbound

This paper cites Medicine 100(31), e26745 (August 2021).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Medicine 100(31), e26745 (August 2021)

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.899730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.939968Z digest=sha256:91e475647481761c3035479cf826ba051e0fad84e26e26d8ebc17c73fa6f8619

Observation e65ff21b-1314-4493-b746-17a25052154a · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.867911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:56.980230Z digest=sha256:6f6c1d9253c05afae85667f55d3d21a8cc3530cb8802a8fb30e4bb00040a5fe1

Observation 39434a35-3cfa-4473-aa4d-893eb451424f · outbound

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

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:57.048098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:57.048098Z digest=sha256:bc104aeff6048f11649930b391a21671701669411879d92dec1d01ffad700376

Observation b0f0fc69-3285-4eb7-88bc-ed7ed342aecd · outbound

This paper cites Cancers 15(10), 2715 (2023).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Cancers 15(10), 2715 (2023)

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.796881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.119011Z digest=sha256:b986ce3df5c9ce21826cb242f795191a4a590efa9ef84834918803dbbbbf528a

Observation 4c935f33-0fea-4c91-8144-f465e5374e88 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:57.148895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:57.148895Z digest=sha256:e8a89cdf50880638faa94c5b5a91d58fa0a01f2e69991457fede4e161f39ab28

Observation 2b8ef2b0-e80b-461f-b1ba-7ce970e24b60 · outbound

This paper cites Cancer treatment reviews40(4), 558–566 (2014).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Cancer treatment reviews40(4), 558–566 (2014)

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.534441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.172130Z digest=sha256:129fb4b36fd7b0dee2c72547af6299f550976327cbf74db872e02a4faa42edb8

Observation 31d93ae5-21d3-4bd0-a040-708ec819d0a7 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.261796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.231444Z digest=sha256:5d2901798293f4fef653c69b01d6ff1df161128f5f6106abfa82d88c956ae32a

Observation 9d0e99ef-1b46-4c9d-a534-138e6768d672 · outbound

This paper cites MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:57.286283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:57.286283Z digest=sha256:4c542a92c23c647f4bc307ecd4b27d37f1c444ff179fe13450cc45d5bacea5ea

Observation b845677e-d738-429d-957b-5dd7e36b3f55 · outbound

This paper cites In: International Title Suppressed Due to Excessive Length 11 Conference on Medical Image Computing and Computer-Assisted Intervention.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: International Title Suppressed Due to Excessive Length 11 Conference on Medical Image Computing and Computer-Assisted Intervention

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:59.057467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.338010Z digest=sha256:bdfd4872badf2a3888f6ddc304d53d6f846b8b0a9dcd14229baa01f1faa22b8d

Observation f8643865-f840-4191-91d0-5ce5eeab4260 · outbound

This paper cites Breast Cancer Re- search and Treatment153, 607–616 (2015).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Breast Cancer Re- search and Treatment153, 607–616 (2015)

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:58.830594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.389252Z digest=sha256:a6985004d98901f5951e6483bdb41535aeb9ae22b9af40018deea3a89aa35ced

Observation 2e455a81-79d5-4e3d-bba7-fc1b378ac175 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:57.453659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:57.453659Z digest=sha256:f8287ea5a70850c1ea4b4e693044bf62abff4b49547b672813c87b1fc8f9c9a0

Observation 4095247d-93f1-41ee-86f8-f42f5d0d3ff8 · outbound

This paper cites Artificial Intelligence Review56(Suppl 1), 857–892 (2023).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation Artificial Intelligence Review56(Suppl 1), 857–892 (2023)

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:58.601606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.506006Z digest=sha256:74b11e67b2510b99b45e384ba3aa7419685ee258f49609582cd11af79fc77764

Observation 9ad1e030-1036-45b9-ac7a-dd3c35926d23 · outbound

This paper cites In: International conference on medical image computing and computer-assisted intervention.

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation In: International conference on medical image computing and computer-assisted intervention

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:58.314995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.540187Z digest=sha256:1cb3455fae2367c8aa67a9bb7f5f4f374e086627dc4643f57d18503d1a0cbe15

Observation a771ed38-0b6a-47a4-b903-e82c3f0269a2 · outbound

This paper cites IEEE Journal of Biomedical and Health Informatics (2024).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation IEEE Journal of Biomedical and Health Informatics (2024)

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:10:58.090498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-06T19:10:57.627413Z digest=sha256:4413fce418b5d3e8e9b1667641a1b2d4a218658d485380443c991ff36ad48506

Observation 9a56a924-f51c-40ad-9046-baeded85aaf1 · outbound

This paper cites International Journal of Computer Vision130(9), 2337–2348 (2022).

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation International Journal of Computer Vision130(9), 2337–2348 (2022)

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T19:10:57.687124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:10:57.687124Z digest=sha256:b5247be8f97fafc7f2f7d531b7b853443f437f11ebfce249963782a2e6391c44

Pith citing papers

No inbound Pith citation observations are available.