Paper Citation Record · LEDGER

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network

As of 20 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:1908.08947.

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

pith.paper-citation-record.v1
1908.08947 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:23:55.897430Z

measured 18 of 18 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

18 of 18 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8dde9b4-0664-4ac5-97fe-f04f09f082a8 · outbound

This paper cites Cancer incidence and mortality worldwide: sources, methods and major patterns in globocan 2012.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Cancer incidence and mortality worldwide: sources, methods and major patterns in globocan 2012

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.122988Z

Source-reported events for the cited work

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Observation fd5fc0ac-3004-45cd-91e8-183d9888b6ff · outbound

This paper cites Advances in arterial spin labelling mri meth- ods for measuring perfusion and collateral ﬂow.Journal of Cerebral Blood Flow & Metabolism, 38(9):1461–1480, 2018.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Advances in arterial spin labelling mri meth- ods for measuring perfusion and collateral ﬂow.Journal of Cerebral Blood Flow & Metabolism, 38(9):1461–1480, 2018

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.111974Z

Source-reported events for the cited work

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Observation bd8c3f34-1703-47f6-be72-1cfc9d7604a3 · outbound

This paper cites The quasar repro- ducibility study, part II: Results from a multi-center arterial spin labeling test– retest study.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network The quasar repro- ducibility study, part II: Results from a multi-center arterial spin labeling test– retest study

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.100536Z

Source-reported events for the cited work

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Observation bc22acc7-e619-4bc7-8db1-bde808411f2c · outbound

This paper cites Esophageal gross tumor volume segmentation using a 3d convolutional neural network.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Esophageal gross tumor volume segmentation using a 3d convolutional neural network

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.089675Z

Source-reported events for the cited work

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Observation b6da923b-8d78-4700-8e7a-b481af8ff4e3 · outbound

This paper cites Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.Medical physics, 2019.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.Medical physics, 2019

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.079547Z

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 9cc2a84b-e2e7-4bcf-9f6c-2255b8d93416 · outbound

This paper cites Iterative pet image reconstruction using convolutional neural network representation.TMI, 38(3):675– 685, 2018.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Iterative pet image reconstruction using convolutional neural network representation.TMI, 38(3):675– 685, 2018

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.069775Z

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 98c7f0d5-506b-4ae8-bdd8-30386ee65a2a · outbound

This paper cites Boosting snr and/or resolution of arterial spin label (ASL) imaging using multi-contrast approaches with multi-lateral guided ﬁlter and deep networks.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Boosting snr and/or resolution of arterial spin label (ASL) imaging using multi-contrast approaches with multi-lateral guided ﬁlter and deep networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.059888Z

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 2d898c67-267c-4f87-a8f5-43954977bd30 · outbound

This paper cites Fan, Mohammad M.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Fan, Mohammad M

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.048946Z

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 168f3ba6-d5b1-4d7f-a875-3887cadc3f49 · outbound

This paper cites AtemporaldeeplearningapproachforMRperfusionparameterestimation in stroke.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network AtemporaldeeplearningapproachforMRperfusionparameterestimation in stroke

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.038808Z

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 b4a8d394-543a-479e-8c79-a08227a8cad0 · outbound

This paper cites Densely connected convolutional networks.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Densely connected convolutional networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.028276Z

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 d199bfa6-f46f-4e6d-ae77-49e916845380 · outbound

This paper cites The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.017540Z

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 54a74216-71a7-4a7c-9de3-fd535f00a922 · outbound

This paper cites Rapid 3d dynamic arterial spin labeling with a sparse model-based image reconstruction.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Rapid 3d dynamic arterial spin labeling with a sparse model-based image reconstruction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:56.005989Z

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 420dc30f-c7f7-4108-ba20-77475d9449aa · outbound

This paper cites Image super- resolution using deep convolutional networks.TPAMI, 38(2):295–307, 2015.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Image super- resolution using deep convolutional networks.TPAMI, 38(2):295–307, 2015

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.994513Z

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 ab6c1f05-7f36-4891-83e5-13a7a79fa40b · outbound

This paper cites Perceptual losses for real-time style transfer and super-resolution.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Perceptual losses for real-time style transfer and super-resolution

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.983231Z

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 bf13341a-c5cf-4f4b-adc1-37846b5b8046 · outbound

This paper cites A general kinetic model for quantitative perfusion imaging with arterial spin labeling.MRM, 40(3):383–396, 1998.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network A general kinetic model for quantitative perfusion imaging with arterial spin labeling.MRM, 40(3):383–396, 1998

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.971696Z

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 60e87f4c-89e7-4ff0-ac29-1fcd52c59119 · outbound

This paper cites Brainweb: Online interface to a 3d mri simulated brain database.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Brainweb: Online interface to a 3d mri simulated brain database

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.959639Z

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 c18a44cb-a76d-46ad-88af-411a30f33f80 · outbound

This paper cites Elastix: a toolbox for intensity-based medical image registration.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Elastix: a toolbox for intensity-based medical image registration

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.947409Z

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 12505fc5-d1d1-4c94-899e-abf31bde5a00 · outbound

This paper cites Transit time mapping in the mouse brain using time- encoded pcasl.

Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network Transit time mapping in the mouse brain using time- encoded pcasl

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:23:55.934556Z

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.