Paper Citation Record · LEDGER

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT

As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.15193.

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

pith.paper-citation-record.v1
2507.15193 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:42:16.430266Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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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

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 8e754e39-8483-48ae-a59c-1b4550163b3a · outbound

This paper cites Endocrine practice 24(1), 78–90 (2018).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Endocrine practice 24(1), 78–90 (2018)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:17.059265Z

Source-reported events for the cited work

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Observation dd8c3eb5-ad08-40a3-8fac-e3aeb235faec · outbound

This paper cites The Lancet 366(9486), 665–675 (2005).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT The Lancet 366(9486), 665–675 (2005)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:17.044136Z

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

Observation 5691891b-4203-4360-9451-4b55cd4686a5 · outbound

This paper cites The Journal of Clinical Endocrinology & Metabolism 90(4), 2110–2116 (2005).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT The Journal of Clinical Endocrinology & Metabolism 90(4), 2110–2116 (2005)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:17.023066Z

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

Observation 29b8d4c5-ad26-4bfc-bcef-559bcb9f13fd · outbound

This paper cites part 1 of 2: advances in pathogenesis and diagnosis of pheochromocytoma and paraganglioma.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT part 1 of 2: advances in pathogenesis and diagnosis of pheochromocytoma and paraganglioma

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:17.005244Z

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Observation a37947b3-ccc9-471b-b853-e1c3dd523578 · outbound

This paper cites Endocrine reviews 45(3), 414–434 (2024).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Endocrine reviews 45(3), 414–434 (2024)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.986283Z

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 f784286d-dafe-48f3-acf7-e660bf6e8649 · outbound

This paper cites Endocrine reviews 43(2), 199–239 (2022).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Endocrine reviews 43(2), 199–239 (2022)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.961899Z

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 469af0c4-1664-4f5e-81e7-a2a7886f16cf · outbound

This paper cites Journal of Molecular Endocrinology 70(3) (2023).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Journal of Molecular Endocrinology 70(3) (2023)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.945176Z

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 06cf5023-d255-4ad7-ad45-d95761c95d37 · outbound

This paper cites Cancers 15(18), 4601 (2023).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Cancers 15(18), 4601 (2023)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.929208Z

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 675c86e2-917a-4589-8f8c-3b0ed2349149 · outbound

This paper cites Current problems in cancer 38(1), 7–41 (2014).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Current problems in cancer 38(1), 7–41 (2014)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.906365Z

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 750da3d6-b15e-4e8e-a7ac-88ad4d86cb2c · outbound

This paper cites Pediatric Nephrology35, 581– 594 (2020).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Pediatric Nephrology35, 581– 594 (2020)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.889489Z

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 873b4541-54b3-4c77-9a1b-9672a25f9498 · outbound

This paper cites Annals of surgical oncology 24, 1546–1550 (2017) 18.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Annals of surgical oncology 24, 1546–1550 (2017) 18

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.873786Z

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 04d4c479-83e8-47d1-8117-f6a94e0cb78e · outbound

This paper cites S ¸i¸ sli Etfal Hastanesi Tip B¨ ulteni54(4), 391–398 (2020).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT S ¸i¸ sli Etfal Hastanesi Tip B¨ ulteni54(4), 391–398 (2020)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.856325Z

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

Observation 9aea792b-3f28-4124-ad62-3076a83e8a92 · outbound

This paper cites American Journal of Roentgenology 194(6), 1450–1460 (2010).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT American Journal of Roentgenology 194(6), 1450–1460 (2010)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.838068Z

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 bed1e243-1355-43b2-86a9-093c57788351 · outbound

This paper cites Radiology 278(2), 563–577 (2016).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Radiology 278(2), 563–577 (2016)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.819090Z

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 d109b778-9d00-4d72-bec2-e10eb582f499 · outbound

This paper cites In: International Workshop on Applications of Medical AI, pp.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: International Workshop on Applications of Medical AI, pp

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.802962Z

Source-reported events for the cited work

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Observation fafab58a-2655-40d4-a7cd-6672ca8bd3b4 · outbound

This paper cites In: Medical Imaging 2025: Computer-Aided Diagnosis, vol.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: Medical Imaging 2025: Computer-Aided Diagnosis, vol

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.787069Z

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 1cf06650-7105-40bc-b1a2-a2eaf62f75bc · outbound

This paper cites Insights into Imaging 16(1), 1–15 (2025).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Insights into Imaging 16(1), 1–15 (2025)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.770675Z

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 a8a1c375-3d6e-4c47-9711-a361e1052c43 · outbound

This paper cites IEEE transactions on medical imaging 34(10), 1993–2024 (2014).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT IEEE transactions on medical imaging 34(10), 1993–2024 (2014)

Reference 18

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Observation f9c2b745-ae65-4a27-90cc-5350991bdfad · outbound

This paper cites Medical image analysis 42, 60–88 (2017).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Medical image analysis 42, 60–88 (2017)

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T15:42:14.425457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b57f743-00ae-4670-a2a5-e07405b70197 · outbound

This paper cites In: Medical Image Computing and Computer- assisted intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18, pp.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: Medical Image Computing and Computer- assisted intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18, pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.726478Z

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 ef347418-f442-4e49-b650-003b82291ad9 · outbound

This paper cites In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.708679Z

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 3f3ef56b-5515-47bd-ab00-71562c2f1009 · outbound

This paper cites In: International MICCAI Brainlesion Workshop, pp.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: International MICCAI Brainlesion Workshop, pp

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.690329Z

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 53a84394-fa82-4336-bb6f-58ab1ba0b514 · outbound

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

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Nature methods 18(2), 203–211 (2021)

Reference 23

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Observation 80ea1b59-4b57-49f4-9d95-8aa67394a759 · outbound

This paper cites Computerized Medical Imaging and Graphics 116, 102419 (2024).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Computerized Medical Imaging and Graphics 116, 102419 (2024)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.661998Z

Source-reported events for the cited work

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Observation 8909464e-bd68-4a8c-9ba8-988a1574c983 · outbound

This paper cites In: SPIE Medical Imaging 2024: Computer-Aided Diagnosis, vol.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT In: SPIE Medical Imaging 2024: Computer-Aided Diagnosis, vol

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.643613Z

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 a9447cc9-f25a-4015-8081-07142126b8e7 · outbound

This paper cites International Journal of Computer Assisted Radiology and Surgery, 1–7 (2024).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT International Journal of Computer Assisted Radiology and Surgery, 1–7 (2024)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.627745Z

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 27163185-8517-40b9-aa55-bec295c23f23 · outbound

This paper cites International journal of computer assisted radiology and surgery 19(8), 1537–1544 (2024).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT International journal of computer assisted radiology and surgery 19(8), 1537–1544 (2024)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.611707Z

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 fed66bea-4804-4664-80ca-b9ee94fe66d1 · outbound

This paper cites Neuroimage 31(3), 1116–1128 (2006).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Neuroimage 31(3), 1116–1128 (2006)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.596144Z

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 9edd65b4-6e10-4423-84ab-137148478dce · outbound

This paper cites Radiology: Artificial Intelligence 5(5), 230024 (2023).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Radiology: Artificial Intelligence 5(5), 230024 (2023)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.579143Z

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 a72434c7-a651-4a71-9d93-b089314da171 · outbound

This paper cites MONAI: An open-source framework for deep learning in healthcare.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT MONAI: An open-source framework for deep learning in healthcare

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T15:42:16.046867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ef69071-6434-4c61-98ca-094506727938 · outbound

This paper cites Medical image analysis 84, 102680 (2023).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Medical image analysis 84, 102680 (2023)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.560309Z

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 7663e6d5-5678-4b2e-b869-91b48dcf4306 · outbound

This paper cites Expert Systems with Applications 238, 122094 (2024) 20.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Expert Systems with Applications 238, 122094 (2024) 20

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.542618Z

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 77da1a79-a2c3-4fcb-a945-57b69f0b1d6b · outbound

This paper cites Nature communications 13(1), 4128 (2022).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Nature communications 13(1), 4128 (2022)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.528318Z

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 77c07df9-9b1a-4552-9b10-1f11450040ce · outbound

This paper cites Frontiers in oncology13, 1248249 (2023).

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT Frontiers in oncology13, 1248249 (2023)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.512216Z

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 e35d2f10-0eed-48bc-a764-7eeda998b98f · outbound

This paper cites multi-lesion imaging biomarkers as predictors of patient survival.

A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT multi-lesion imaging biomarkers as predictors of patient survival

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:42:16.496863Z

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

No inbound Pith citation observations are available.