Paper Citation Record · LEDGER

Staining normalization in histopathology: Method benchmarking using multicenter dataset

As of 20 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2506.19106.

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

pith.paper-citation-record.v1
2506.19106 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:39:54.683242Z

measured 51 of 51 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T00:55:07.282767Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T00:56:14.095620Z

Reference resolution

50 of 50 outbound references displayed

verified exact0
verified fuzzy35
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da4affc8-c2dd-4d33-8daf-2aaa63816fc9 · outbound

This paper cites W., Ciovacco, W.

Staining normalization in histopathology: Method benchmarking using multicenter dataset W., Ciovacco, W

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.248001Z

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Observation 548d7eb7-e714-44d0-bda4-88091d23d1b0 · outbound

This paper cites A.et al.Impact of preanalytical factors during histology processing on section suitability for digital image analysis.Toxicol.

Staining normalization in histopathology: Method benchmarking using multicenter dataset A.et al.Impact of preanalytical factors during histology processing on section suitability for digital image analysis.Toxicol

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.236132Z

Source-reported events for the cited work

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Observation c840172d-2ce6-40d9-839e-5b365b982eb4 · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:55.225101Z

Source-reported events for the cited work

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Observation c4bad443-d9d6-4495-8c2a-793c97e7d8aa · outbound

This paper cites S.et al.Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future.

Staining normalization in histopathology: Method benchmarking using multicenter dataset S.et al.Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.212191Z

Source-reported events for the cited work

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Observation b997fc0e-362a-4f7f-b067-e8154b5bfc1a · outbound

This paper cites Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T18:39:54.729640Z

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 497b558d-4af0-47ab-83e5-3c937318282f · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:55.200177Z

Source-reported events for the cited work

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Observation 6caa1157-3a34-424a-94da-27cb2ceb017d · outbound

This paper cites A.et al.Current and future applications of artificial intelligence in pathology: a clinical perspective.J.

Staining normalization in histopathology: Method benchmarking using multicenter dataset A.et al.Current and future applications of artificial intelligence in pathology: a clinical perspective.J

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.189464Z

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 755c5b7e-f99f-43da-8ad4-20d9b54d5e6a · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 9

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Observation e1ec6cf6-f146-4d70-9f6a-b4b80f71d66f · outbound

This paper cites L.et al.Access to pathology and laboratory medicine services: a crucial gap.The Lancet391, 1927–1938 (2018).

Staining normalization in histopathology: Method benchmarking using multicenter dataset L.et al.Access to pathology and laboratory medicine services: a crucial gap.The Lancet391, 1927–1938 (2018)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.168350Z

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Observation 36490e2b-e75c-4274-b22d-2a539f3cf153 · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:55.156388Z

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 cbf98764-577f-4bb8-b3fe-d0277d0785b3 · outbound

This paper cites C.et al.Deep learning assisted mitotic counting for breast cancer.Lab.

Staining normalization in histopathology: Method benchmarking using multicenter dataset C.et al.Deep learning assisted mitotic counting for breast cancer.Lab

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.145107Z

Source-reported events for the cited work

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Observation 4d730221-dac9-4772-a7d2-7c3518a3c6b2 · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:55.133829Z

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Observation aba1fea8-f5d7-46a4-96d6-8bfb62cf6679 · outbound

This paper cites D.et al.Methods for segmentation and classification of digital microscopy tissue images.Front.

Staining normalization in histopathology: Method benchmarking using multicenter dataset D.et al.Methods for segmentation and classification of digital microscopy tissue images.Front

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.122335Z

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Observation 96836bc2-98d1-497b-a5aa-e4788891f337 · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:55.111633Z

Source-reported events for the cited work

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Observation b5ff46a5-4125-4db2-827d-9ffdcd53578d · outbound

This paper cites Hepatology72, 2000–2013 (2020).

Staining normalization in histopathology: Method benchmarking using multicenter dataset Hepatology72, 2000–2013 (2020)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.098953Z

Source-reported events for the cited work

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Observation 0969b285-4eb2-4384-813b-ec53ab12e2ad · outbound

This paper cites cancer1, 800–810 (2020).

Staining normalization in histopathology: Method benchmarking using multicenter dataset cancer1, 800–810 (2020)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.085584Z

Source-reported events for the cited work

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Observation 57c8ea2c-2126-4ea0-b8f8-5ea04794ff3e · outbound

This paper cites Pathol.19, 42 (2024).

Staining normalization in histopathology: Method benchmarking using multicenter dataset Pathol.19, 42 (2024)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.073958Z

Source-reported events for the cited work

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Observation cbe5a54b-7faf-4118-afec-09bdb0aed4f1 · outbound

This paper cites & Orsi, N.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Orsi, N

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.061960Z

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 62c131e8-f985-415b-9799-7a37d6174f1f · outbound

This paper cites & Doyle, S.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Doyle, S

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.051277Z

Source-reported events for the cited work

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Observation ad471539-cbad-4a7d-b906-4c3f22a6e646 · outbound

This paper cites image analysis58, 101544 (2019).

Staining normalization in histopathology: Method benchmarking using multicenter dataset image analysis58, 101544 (2019)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.040816Z

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 e1e26670-a9e0-4b33-85b0-661090c84bbe · outbound

This paper cites 25.Goodfellow, I.et al.Generative adversarial nets.Adv.

Staining normalization in histopathology: Method benchmarking using multicenter dataset 25.Goodfellow, I.et al.Generative adversarial nets.Adv

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.029010Z

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 fce3a98f-6ea1-4a59-8770-61fca4b90094 · outbound

This paper cites & Shirley, P.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Shirley, P

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.017537Z

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 098536fb-737a-4461-8570-d64d085cbc9e · outbound

This paper cites In2009 IEEE international symposium on biomedical imaging: from nano to macro, 1107–1110 (IEEE, 2009).

Staining normalization in histopathology: Method benchmarking using multicenter dataset In2009 IEEE international symposium on biomedical imaging: from nano to macro, 1107–1110 (IEEE, 2009)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:55.005146Z

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 0af50615-1152-43d0-8a91-c15e0f45cf9b · outbound

This paper cites 29.Gonzalez, R.

Staining normalization in histopathology: Method benchmarking using multicenter dataset 29.Gonzalez, R

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.993489Z

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 7769efb2-6107-45b1-9be9-35533c25c1ae · outbound

This paper cites InProc Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy (MICCAI Workshop), vol.

Staining normalization in histopathology: Method benchmarking using multicenter dataset InProc Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy (MICCAI Workshop), vol

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.982890Z

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 46ce2b85-fcbc-409d-a0ad-8bb633aa771a · outbound

This paper cites & Thomas, N.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Thomas, N

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.971553Z

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 627f37c3-8f12-4183-8b03-c53c6f056ec8 · outbound

This paper cites an unresolved cited work.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:39:54.960702Z

Source-reported events for the cited work

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Observation 0e50861b-14a7-49fd-8186-93bdeaccec73 · outbound

This paper cites & Efros, A.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Efros, A

Reference 33

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Source-reported events for the cited work

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Observation f73e79bf-80e2-4427-895b-4512cf38185e · outbound

This paper cites J., Jackson, C.

Staining normalization in histopathology: Method benchmarking using multicenter dataset J., Jackson, C

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.943413Z

Source-reported events for the cited work

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Observation c2db659d-1cf4-4877-aa04-fe473d9f90bb · outbound

This paper cites M., Boor, P.

Staining normalization in histopathology: Method benchmarking using multicenter dataset M., Boor, P

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.932356Z

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 679fd001-b9dd-41f2-924a-a72bb0e58f17 · outbound

This paper cites & Latonen, L.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Latonen, L

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.921426Z

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Observation 24b9ee37-5cd4-4833-9c82-43bd6294cbbe · outbound

This paper cites & Ruusuvuori, P.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Ruusuvuori, P

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.910496Z

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 0c0f42f3-bd8d-4039-b014-090ff0048284 · outbound

This paper cites & Bueno, G.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Bueno, G

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.898033Z

Source-reported events for the cited work

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Observation 986c9d91-2f86-47e9-907f-1045c7ddd930 · outbound

This paper cites & Brox, T.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Brox, T

Reference 39

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Source-reported events for the cited work

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Observation 789d424a-24fa-411e-b597-01363ce165c5 · outbound

This paper cites & Litjens, G.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Litjens, G

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.880278Z

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 62606a40-9a3a-4669-9cfe-2e208dadffb0 · outbound

This paper cites & Litjens, G.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Litjens, G

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.869620Z

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 e4de3470-94b5-4269-ae57-de981db9d5fb · outbound

This paper cites & Efros, A.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Efros, A

Reference 42

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Source-reported events for the cited work

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Observation 51ee7024-8df0-43c4-99a1-2474d21db909 · outbound

This paper cites & Chalechale, A.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Chalechale, A

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.852396Z

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 e3d01735-4329-4ffb-a537-eeb796630d08 · outbound

This paper cites T., Baur, C., Navab, N.

Staining normalization in histopathology: Method benchmarking using multicenter dataset T., Baur, C., Navab, N

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.840225Z

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 2972c35b-701b-42e7-997f-9da0653df6f3 · outbound

This paper cites Neural Stain-Style Transfer Learning using GAN for Histopathological Images.

Staining normalization in histopathology: Method benchmarking using multicenter dataset Neural Stain-Style Transfer Learning using GAN for Histopathological Images

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T18:39:54.645110Z

Source-reported events for the cited work

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Observation f17c8107-5c9a-43fa-9981-9f68a05e7803 · outbound

This paper cites & Hamarneh, G.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Hamarneh, G

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.828819Z

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

Observation f447feb9-49f5-4332-ad85-155bb0288619 · outbound

This paper cites & Sun, J.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Sun, J

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T18:39:54.653174Z

Source-reported events for the cited work

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Observation 28571669-6087-4e66-bc88-fce8bfe7658c · outbound

This paper cites C.et al.Image technology colour management-architecture, profile format, and data structure.Specif.

Staining normalization in histopathology: Method benchmarking using multicenter dataset C.et al.Image technology colour management-architecture, profile format, and data structure.Specif

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.811768Z

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 337971f6-1ec6-4671-82ef-e52268dac202 · outbound

This paper cites & Wojna, Z.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Wojna, Z

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T18:39:54.660067Z

Source-reported events for the cited work

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Observation 54c2bad7-0f8e-4d75-a55c-3f3a5fd1edd2 · outbound

This paper cites & Hochreiter, S.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Hochreiter, S

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T18:39:54.664716Z

Source-reported events for the cited work

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Observation 6249212d-4fac-4eca-98e9-2ec1c9cc88bf · outbound

This paper cites & Zhang, D.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Zhang, D

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.786664Z

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 f859c24a-15f8-494c-bde5-19bde8cf034f · outbound

This paper cites & Kuopio, T.

Staining normalization in histopathology: Method benchmarking using multicenter dataset & Kuopio, T

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.775906Z

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 f301c284-e7c7-4913-a7f5-52e5f1652fdc · outbound

This paper cites T., Tessema, A.

Staining normalization in histopathology: Method benchmarking using multicenter dataset T., Tessema, A

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.764856Z

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 ed17bf9c-ec5a-4b23-86c0-0fbf24709808 · outbound

This paper cites W., Zewde, E.

Staining normalization in histopathology: Method benchmarking using multicenter dataset W., Zewde, E

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.752806Z

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 730e841b-8091-4228-b82d-64cb25f80554 · outbound

This paper cites InProceedings of the fifth Berkeley symposium on mathematical statistics and probability, 14, 281–297 (Oakland, CA, USA, 1967).

Staining normalization in histopathology: Method benchmarking using multicenter dataset InProceedings of the fifth Berkeley symposium on mathematical statistics and probability, 14, 281–297 (Oakland, CA, USA, 1967)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:39:54.741475Z

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

Observation b687c26a-3fcf-44ee-a13f-5e78b9fbc155 · inbound

Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI cites this paper.

Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI Staining normalization in histopathology: Method benchmarking using multicenter dataset

Reference 12

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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.