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Paper Citation Record · LEDGER

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.14046.

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

pith.paper-citation-record.v1
2507.14046 v1

Coverage vector

measured 35 of 35 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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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 8dd9be86-6031-4d25-9166-5bc249d14637 · outbound

This paper cites Pulmonary functional imaging: Part 1—state-of-the-art technical and physiologic underpinnings,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Pulmonary functional imaging: Part 1—state-of-the-art technical and physiologic underpinnings,

Reference 1

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Observation 50200f9a-dd66-4493-8a91-e1ae75138183 · outbound

This paper cites Pulmonary functional imaging: part 2—state-of-the- art clinical applications and opportunities for improved patient care,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Pulmonary functional imaging: part 2—state-of-the- art clinical applications and opportunities for improved patient care,

Reference 2

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Observation 226ed7a7-d38b-472a-92f7-3637287f4d12 · outbound

This paper cites Deep learning to quantify pulmonary edema in chest radiographs,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Deep learning to quantify pulmonary edema in chest radiographs,

Reference 3

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Observation 3780d339-3b3b-4589-b975-c50bfe9b2e0e · outbound

This paper cites Imaging the acute respiratory distress syndrome: past, present and future,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Imaging the acute respiratory distress syndrome: past, present and future,

Reference 4

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Observation 63869e3b-d01c-4114-a0ce-db5a34eed27c · outbound

This paper cites Imaging advances in chronic obstructive pulmonary disease. insights from the genetic epidemiology of chronic obstructive pulmonary disease (copdgene) study,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Imaging advances in chronic obstructive pulmonary disease. insights from the genetic epidemiology of chronic obstructive pulmonary disease (copdgene) study,

Reference 5

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Observation 4b70b6b6-5b81-420f-b715-4aa8b2c8bc6c · outbound

This paper cites Computer-aided diagnosis of pulmonary fibrosis using deep learning and ct images,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Computer-aided diagnosis of pulmonary fibrosis using deep learning and ct images,

Reference 6

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Observation 437a6521-2094-448a-985d-671d9cbac0cc · outbound

This paper cites Expanding applications of pulmonary mri in the clinical evaluation of lung disor- ders: Fleischner society position paper,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Expanding applications of pulmonary mri in the clinical evaluation of lung disor- ders: Fleischner society position paper,

Reference 7

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Observation c4866aba-8632-4446-80d0-4c82d6f094aa · outbound

This paper cites Overview of mri for pulmonary functional imaging,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Overview of mri for pulmonary functional imaging,

Reference 8

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Observation 8fd74b15-5f2c-4714-870c-31b4b8aeff5e · outbound

This paper cites Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam ct imaging,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam ct imaging,

Reference 9

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Observation 434a8728-50f2-46b2-9f51-e9ee2dc02081 · outbound

This paper cites Eichler, J.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Eichler, J

Reference 10

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Observation be5faeda-e495-49ed-900a-8cb85bff2fa9 · outbound

This paper cites Supervised descent learning for thoracic electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Supervised descent learning for thoracic electrical impedance tomography,

Reference 11

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Observation 4fe08e2b-e7cf-44d4-ac4f-b9922edb45cc · outbound

This paper cites Early screening of lung function by electrical impedance tomography in people with normal spirometry reveals unrecognized pathological features,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Early screening of lung function by electrical impedance tomography in people with normal spirometry reveals unrecognized pathological features,

Reference 12

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Observation 404b219a-4126-4c30-b14f-63f8f3b03b06 · outbound

This paper cites Multi-modal eit imaging using lensfree and flexible impedance sensor,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Multi-modal eit imaging using lensfree and flexible impedance sensor,

Reference 13

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Observation 614433b8-abbd-4acd-b899-217b2abf90aa · outbound

This paper cites Three- dimensional electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Three- dimensional electrical impedance tomography,

Reference 14

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Observation ce457c98-11d7-4b91-961d-7aa70146e987 · outbound

This paper cites Tikhonov regularization and prior information in electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Tikhonov regularization and prior information in electrical impedance tomography,

Reference 15

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Observation d6fcce1a-e8c0-4bf6-bf35-972a2fcd38c0 · outbound

This paper cites Adaptive l {p} regu- larization for electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Adaptive l {p} regu- larization for electrical impedance tomography,

Reference 16

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Observation 319ffe8a-758e-4500-b9fa-7f1fb95dc8db · outbound

This paper cites In vivo impedance imaging with total variation regularization,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging In vivo impedance imaging with total variation regularization,

Reference 17

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Observation da4b31b3-e580-4582-b561-09f33228029e · outbound

This paper cites Deep d-bar: Real-time electrical impedance tomography imaging with deep neural networks,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Deep d-bar: Real-time electrical impedance tomography imaging with deep neural networks,

Reference 18

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Observation 465650ca-31ff-45e3-b0e3-a3b6a4118fec · outbound

This paper cites Image reconstruction based on convolutional neural network for electrical resistance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Image reconstruction based on convolutional neural network for electrical resistance tomography,

Reference 19

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Observation d457a0e8-6fd3-48d1-bb5b-97ac2ee6642b · outbound

This paper cites Electrical resistance tomography image reconstruction with densely connected convolutional neural network,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Electrical resistance tomography image reconstruction with densely connected convolutional neural network,

Reference 20

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Observation b504ceb6-b97f-4093-9457-8a61a60fb694 · outbound

This paper cites A learning- based method for solving ill-posed nonlinear inverse problems: A simulation study of lung eit,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging A learning- based method for solving ill-posed nonlinear inverse problems: A simulation study of lung eit,

Reference 21

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Observation b98888fc-e028-432e-b711-11dc86891b52 · outbound

This paper cites Electrical resistance tomography with conditional generative adversarial networks,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Electrical resistance tomography with conditional generative adversarial networks,

Reference 22

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Observation e635cbdd-5856-42a9-8ce9-23f1dee295cb · outbound

This paper cites Multi-frequency Electrical Impedance Tomography Reconstruction with Multi-Branch Attention Image Prior.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Multi-frequency Electrical Impedance Tomography Reconstruction with Multi-Branch Attention Image Prior

Reference 23

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Observation a942cde3-1145-4e1d-9d7c-f98bddb4dbb3 · outbound

This paper cites Deepeit: Deep image prior enabled electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Deepeit: Deep image prior enabled electrical impedance tomography,

Reference 24

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Observation 4c668514-1659-482f-8b8c-1fa5b2f32e91 · outbound

This paper cites Regular- ized shallow image prior for electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Regular- ized shallow image prior for electrical impedance tomography,

Reference 25

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Source-reported events for the cited work

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Observation 557f6091-309c-49c0-9a30-b7b3c2afdb23 · outbound

This paper cites A multi-frequency electrical impedance tomog- raphy system for real-time 2d and 3d imaging,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging A multi-frequency electrical impedance tomog- raphy system for real-time 2d and 3d imaging,

Reference 26

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Observation c88ef0b8-1d8d-4574-a030-9295cea61b87 · outbound

This paper cites Time sequence learning for electrical impedance tomography using bayesian spatiotemporal priors,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Time sequence learning for electrical impedance tomography using bayesian spatiotemporal priors,

Reference 27

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Source-reported events for the cited work

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Observation 26919026-4e9f-426c-81f7-d115bf26f0f8 · outbound

This paper cites Mmv-net: A multi- ple measurement vector network for multifrequency electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Mmv-net: A multi- ple measurement vector network for multifrequency electrical impedance tomography,

Reference 28

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Observation c68fb43a-8512-46b3-938c-edd1e00fb28a · outbound

This paper cites Multi-path fusion in sfcf-net for enhanced multi-frequency electrical impedance tomography,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Multi-path fusion in sfcf-net for enhanced multi-frequency electrical impedance tomography,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9fef35c3-4a5c-44e5-827c-15430e1ab70c · outbound

This paper cites Dual-modal image reconstruction for electrical impedance tomography with over- lapping group lasso and laplacian regularization,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Dual-modal image reconstruction for electrical impedance tomography with over- lapping group lasso and laplacian regularization,

Reference 30

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Source-reported events for the cited work

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Observation 8cb5bcd8-ce56-4416-b356-b03d3dbbbb37 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Adam: A Method for Stochastic Optimization

Reference 31

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Observation 158a1df6-3ec5-4cb0-8de2-8085b9c408a1 · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Xception: Deep learning with depthwise separable convolu- tions,

Reference 32

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Observation af99678f-2dad-4d72-bb20-68b2515dc171 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,

Reference 33

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Observation 5c25e9cf-7cb2-4cae-a909-fac300c11109 · outbound

This paper cites Squeeze-and-excitation networks,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Squeeze-and-excitation networks,

Reference 34

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unresolved
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Observation d32352c1-ddb7-4e70-bef6-49140daafd14 · outbound

This paper cites Spatial pyramid pooling in deep convolutional networks for visual recognition,.

D2IP: Deep Dynamic Image Prior for 3D Time-sequence Pulmonary Impedance Imaging Spatial pyramid pooling in deep convolutional networks for visual recognition,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-06T16:16:49.190819Z

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Pith citing papers

No inbound Pith citation observations are available.