Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-30T17:55:44.376276Z
Paper Citation Record · LEDGER
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction
As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2605.24012.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
34 of 34 outbound references displayed
- verified exact1
- verified fuzzy25
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation acb15ad1-6f31-4a45-9d07-4584eda36663 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.176440Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 905a21ec-0ec9-485e-89c2-3a5bd8528db8 · outbound
This paper cites For stenosis detection network, the training set contained opacified frames with manually annotated bounding boxes.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction For stenosis detection network, the training set contained opacified frames with manually annotated bounding boxes
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.145895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8c745dee-1bf6-4a99-ba8f-e5b5ae2563b9 · outbound
This paper cites Cardiologists selected contrast -opacified frames from angiograms.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Cardiologists selected contrast -opacified frames from angiograms
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.191159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ed311ee2-f5c3-4c58-aab7-c86de7af64c0 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.193332Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a0f38aec-1594-4bab-9583-6ae02c945045 · outbound
This paper cites 5.1 Technical validation: agreement versus manual TMPFC The sequences from 30 test cases of group B were used for this analysis.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction 5.1 Technical validation: agreement versus manual TMPFC The sequences from 30 test cases of group B were used for this analysis
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.140988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 216ac1d7-faa7-4159-a8fa-2501737b1a82 · outbound
This paper cites Quantitative evaluation revealed outstanding detection accuracy, with mAP50 reaching 0.991, indicating near-flawless stenosis identification.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Quantitative evaluation revealed outstanding detection accuracy, with mAP50 reaching 0.991, indicating near-flawless stenosis identification
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.186228Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation add54603-4b78-4384-9a05-8e8f73cf609c · outbound
This paper cites Qualitative assessment across all the test datasets, mean Likert score was 4.5 with 82% rated more than 4.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Qualitative assessment across all the test datasets, mean Likert score was 4.5 with 82% rated more than 4
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.213993Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8a667f8a-b303-43ce-b5bb-3867e1766222 · outbound
This paper cites The median filter window size for 𝐹1, 𝐹2 was 4% of the sequence length, with a maximum of 3 and a maximum of 11 (odd numbers only).
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction The median filter window size for 𝐹1, 𝐹2 was 4% of the sequence length, with a maximum of 3 and a maximum of 11 (odd numbers only)
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.183350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 40ad6df8-ae6d-4e57-a15b-afbae81a9379 · outbound
This paper cites As detailed in Figure 6(a), the Bland -Altman analysis revealed a mean bias of -0.93 frames, with 95% limits of agreement (LoA) ranging from -5.33 to +3.47 frames.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction As detailed in Figure 6(a), the Bland -Altman analysis revealed a mean bias of -0.93 frames, with 95% limits of agreement (LoA) ranging from -5.33 to +3.47 frames
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.188842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ea21a8dc-3d74-4cdb-a512-4bb195bfa0e8 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.174294Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7769bf1e-0c66-40c3-85a4-a58365fd895d · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.209599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 390379e5-3eda-4d55-a3d6-32273a9c53f8 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.143422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1f8ac84d-c8fe-440a-a1b3-ac90176ce969 · outbound
This paper cites YQH: Data curation, Software, Formal analysis, Resources.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction YQH: Data curation, Software, Formal analysis, Resources
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.195592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 62533a42-28d9-4b9a-9c35-2109e5e2f3de · outbound
This paper cites G., Berry C., Escaned J., Maas A.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction G., Berry C., Escaned J., Maas A
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.198040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6faff596-b5e2-4b5b-ab77-c07f8771619f · outbound
This paper cites A., FFR, iFR, CFR, and IMR: Results from clinical trials., Cardiovasc Revasc Med, 2025, 71: 16-21.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction A., FFR, iFR, CFR, and IMR: Results from clinical trials., Cardiovasc Revasc Med, 2025, 71: 16-21
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.180903Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e4ea18ce-9189-4fb0-8ad8-bb532da6120f · outbound
This paper cites P., et al., TIMI Myocardial Perfusion Frame Count: A New Method to Assess Myocardial Perfusion and Its Predictive Value for Short-Term Prognosis.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction P., et al., TIMI Myocardial Perfusion Frame Count: A New Method to Assess Myocardial Perfusion and Its Predictive Value for Short-Term Prognosis
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.200303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5d67a7c3-7cbc-40e2-b86f-e2c3f02ded84 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.204746Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8705fa0f-9971-4dfe-806e-3e02c2daf702 · outbound
This paper cites D., Ostovaneh M.
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.211669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b840de98-2984-4db8-b174-da83141bbfff · outbound
This paper cites BMC Cardiovasc Disord, 2023, 23, 407.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction BMC Cardiovasc Disord, 2023, 23, 407
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.207164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 853ec02a-7ca5-4927-9245-19852b0d3acf · outbound
This paper cites Github, 2015.
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.167003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e5f9f3a5-61cf-43b3-bfd2-e8ca249f0d7a · outbound
This paper cites L., Interrater reliability: the kappa statistic., Biochem Med (Zagreb), 2012, 22(3): 276-82.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction L., Interrater reliability: the kappa statistic., Biochem Med (Zagreb), 2012, 22(3): 276-82
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.169540Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 38e81c99-e82a-409e-9388-3a7fab914e13 · outbound
This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction YOLOv12: Attention-Centric Real-Time Object Detectors
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T18:04:57.523354Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1be1e63f-19d9-4412-807e-080f60a30403 · outbound
This paper cites Int J Comput Vis, 2010, 88: 303-338.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Int J Comput Vis, 2010, 88: 303-338
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.171775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cb0a3fb4-3a63-4265-bf3c-bf0e4229dd42 · outbound
This paper cites H., Yang T.
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.178593Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 02b7b4af-0bc4-4fea-8a5c-fc3440b35b9a · outbound
This paper cites A., Gao Y., Gerig G., ITK-SNAP: An interactive tool for semi -automatic segmentation of multi -modality biomedical images.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction A., Gao Y., Gerig G., ITK-SNAP: An interactive tool for semi -automatic segmentation of multi -modality biomedical images
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.160367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e60cc61a-3391-4c54-ab11-305ef04775c9 · outbound
This paper cites H., Zhou M., Liu D., Yan Z.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction H., Zhou M., Liu D., Yan Z
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.157856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6c458bc9-8f60-4336-823b-a21ac9a9fc7d · outbound
This paper cites Archives of Psychology, 1932, 140: 1-55.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Archives of Psychology, 1932, 140: 1-55
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.162574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9037bfe3-fddc-483f-9816-d9aa5d2a1969 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.151925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0939aef4-168a-496d-ba77-df65c9741a64 · outbound
This paper cites M., Altman D.
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.153705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f7850022-1e54-483a-bcd3-0d31c9a24cb5 · outbound
This paper cites an unresolved cited work.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction Unresolved cited work
Reference 30
- Resolution
- unresolved
- raw_fallback, observed 2026-07-08T06:54:45.147793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 07cac13b-754e-416e-902a-8f4376e288d3 · outbound
This paper cites H., Knatterud G., Roberts R., Border J., Cohen L.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction H., Knatterud G., Roberts R., Border J., Cohen L
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.149934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8f292aff-2287-40d7-a09f-53d7e3970849 · outbound
This paper cites M., Cannon C.
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.155748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 79031de3-bd7a-44eb-bc97-88b4b979c219 · outbound
This paper cites R., Use and misuse of the receiver operating characteristic curve in risk prediction.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction R., Use and misuse of the receiver operating characteristic curve in risk prediction
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.138032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8e95aef6-3bbe-4984-ad0f-36795767a8bb · outbound
This paper cites A., Nonparametric Statistical Methods., 3rd ed., Wiley, 2013.
Deep Learning-Based Automated Quantification of TIMI Myocardial Perfusion Frame Count (DL-TMPFC) from Coronary Angiography: A Novel Framework for Rapid Assessment of Microvascular Dysfunction A., Nonparametric Statistical Methods., 3rd ed., Wiley, 2013
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-08T06:54:45.164874Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.