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Paper Citation Record · LEDGER

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine

As of 8 August 2026, this Paper Citation Record lists 93 of 93 outbound references and 1 inbound Pith citation observation for arXiv:2506.02149.

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

pith.paper-citation-record.v1
2506.02149 v1

Coverage vector

measured 93 of 93 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:34:03.195506Z

measured 94 of 94 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T02:30:40.372846Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

93 of 93 outbound references displayed

  • verified exact2
  • verified fuzzy58
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ecdad42-da30-429e-b118-8e9d54ba3adc · outbound

This paper cites Projected lifetime cancer risks from current computed tomography imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Projected lifetime cancer risks from current computed tomography imaging,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ab24d005-7bec-4cd8-b9a3-9398e749aa8b · outbound

This paper cites an unresolved cited work.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Unresolved cited work

Reference 2

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Unavailable: canonical work link unavailable.

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Observation 466c9386-eced-4d08-9fb6-c41e1e752dcd · outbound

This paper cites Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography,

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 159e24ba-0e01-4362-ac52-efd29239608f · outbound

This paper cites Simultaneous iterative reconstruction technique: Physical interpretation based on the generalized least squares solution,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Simultaneous iterative reconstruction technique: Physical interpretation based on the generalized least squares solution,

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6e293be5-17a6-4e6a-bed7-63270d481c8b · outbound

This paper cites Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm,

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5dd18f71-ab6d-449b-9a8a-0b53c57973b3 · outbound

This paper cites Maximum likelihood from incomplete data via the EM algorithm,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Maximum likelihood from incomplete data via the EM algorithm,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1b43998c-93bf-4872-8c23-86803c44a264 · outbound

This paper cites Ray contribution masks for structure adaptive sinogram filtering,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Ray contribution masks for structure adaptive sinogram filtering,

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0b03c1b3-33c3-4ce6-96f9-b23b3bc468e2 · outbound

This paper cites Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT,

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d2f6632d-e0f8-4b26-8dba-247cdccf0cb2 · outbound

This paper cites Image reconstruction from projections: Iii. projection completion methods (theory).

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Image reconstruction from projections: Iii. projection completion methods (theory)

Reference 9

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no resolver link, observed 2026-08-07T11:33:52.292706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b421945c-e46c-47de-b668-c12372b8980d · outbound

This paper cites Reduction of ct artifacts caused by metallic implants.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Reduction of ct artifacts caused by metallic implants

Reference 10

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unresolved
no resolver link, observed 2026-08-07T11:33:52.430662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c9329844-13a1-4d8b-ae91-0204223948d7 · outbound

This paper cites Normalized metal artifact reduction (nmar) in computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Normalized metal artifact reduction (nmar) in computed tomography,

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9c867627-dcb2-488f-9fd5-b7db28fe8024 · outbound

This paper cites Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose x-ray computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose x-ray computed tomography,

Reference 12

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Unavailable: canonical work link unavailable.

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Observation ef7a8905-922e-48d5-8923-ca704f78955d · outbound

This paper cites A sinogram denoising algorithm for low-dose computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A sinogram denoising algorithm for low-dose computed tomography,

Reference 13

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e4d3bf10-0036-4cd8-a28a-6df096c62b40 · outbound

This paper cites Metal artifact reduction in ct images by sinogram tv inpainting,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Metal artifact reduction in ct images by sinogram tv inpainting,

Reference 14

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Source-reported events for the cited work

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Observation 8dfb1ba2-67f6-4353-a2c5-49c6e9e315fb · outbound

This paper cites Metal artifact reduction in dual energy ct by sinogram segmentation based on active contour model and tv inpainting,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Metal artifact reduction in dual energy ct by sinogram segmentation based on active contour model and tv inpainting,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5633e911-7626-43f0-9e84-7604dbcc12c5 · outbound

This paper cites A new ct metal artifacts reduction algorithm based on fractional-order sinogram inpainting,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A new ct metal artifacts reduction algorithm based on fractional-order sinogram inpainting,

Reference 16

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 48128e3f-5c6b-4a8d-8ccc-0852b9613988 · outbound

This paper cites Total variation based iterative image reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Total variation based iterative image reconstruction,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c339484e-1293-422a-a116-1d2a13d83ec2 · outbound

This paper cites Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c813cbd7-43f9-40d6-bc17-853d876639e5 · outbound

This paper cites Few-view image reconstruction combining total variation and a high- order norm,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Few-view image reconstruction combining total variation and a high- order norm,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 309e7c07-73fc-42ba-b13a-f67ec9264d54 · outbound

This paper cites Sparse-view X-ray CT reconstruction via total generalized variation regularization,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Sparse-view X-ray CT reconstruction via total generalized variation regularization,

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 91cdf2ef-8b29-450e-8bc7-c1890981916f · outbound

This paper cites Few-view image reconstruc- tion with fractional-order total variation,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Few-view image reconstruc- tion with fractional-order total variation,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 797fa537-b0fd-40df-8529-b9e6e30a42fa · outbound

This paper cites Low-dose spectral CT reconstruction using image gradientℓ 0–norm and tensor dictionary,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose spectral CT reconstruction using image gradientℓ 0–norm and tensor dictionary,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 815f0177-9eeb-47e8-b9de-656cc785e851 · outbound

This paper cites A high-quality photon- counting CT technique based on weight adaptive total-variation and image-spectral tensor factorization for small animals imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A high-quality photon- counting CT technique based on weight adaptive total-variation and image-spectral tensor factorization for small animals imaging,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 121a04d3-2338-44db-979a-e60d5cf2a51d · outbound

This paper cites Low-dose X-ray CT reconstruction via dictionary learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose X-ray CT reconstruction via dictionary learning,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7849766e-021c-49ef-a29c-ef338f8baec7 · outbound

This paper cites Sparse-view spectral ct reconstruction using spectral patch- based low-rank penalty,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Sparse-view spectral ct reconstruction using spectral patch- based low-rank penalty,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a9c37744-04b6-46c5-9d43-57dae1c39acd · outbound

This paper cites Convolutional sparse coding for compressed sensing CT reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Convolutional sparse coding for compressed sensing CT reconstruction,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8faec244-0315-46e0-aa6d-d62ebd9c8ea0 · outbound

This paper cites Spectral CT reconstruction with image sparsity and spectral mean,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Spectral CT reconstruction with image sparsity and spectral mean,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0fa184bc-09b9-488e-a657-ee7d858ea72f · outbound

This paper cites Sparse-view X- ray CT reconstruction usingℓ 1 regularization with learned sparsifying transform,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Sparse-view X- ray CT reconstruction usingℓ 1 regularization with learned sparsifying transform,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fc020209-ec82-44ef-b4a0-a86930af30ba · outbound

This paper cites Spectral ct reconstruction—assist: Aided by self-similarity in image- spectral tensors,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Spectral ct reconstruction—assist: Aided by self-similarity in image- spectral tensors,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation cd6e996b-b6fa-428c-b1d8-ae4c31a8c5c6 · outbound

This paper cites Font-sir: Fourth-order nonlocal tensor decomposition model for spectral ct image reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Font-sir: Fourth-order nonlocal tensor decomposition model for spectral ct image reconstruction,

Reference 30

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b27adde8-ea71-45e8-8feb-0842c7b299fe · outbound

This paper cites Bayesian statistical reconstruction for low-dose X-ray computed tomography using an adaptive-weighting nonlocal prior,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Bayesian statistical reconstruction for low-dose X-ray computed tomography using an adaptive-weighting nonlocal prior,

Reference 31

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raw_fallback, observed 2026-08-07T11:34:14.170745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 072383a7-854c-455c-ab1c-461b2d0f1218 · outbound

This paper cites Iterative deblurring for ct metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Iterative deblurring for ct metal artifact reduction,

Reference 32

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 23777df2-95bd-4a57-915b-aaec8d056f34 · outbound

This paper cites Iterative image reconstruction for cerebral perfusion ct using a pre- contrast scan induced edge-preserving prior,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Iterative image reconstruction for cerebral perfusion ct using a pre- contrast scan induced edge-preserving prior,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f8b68192-7a53-4687-8027-7cc02439544c · outbound

This paper cites A perspective on deep imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A perspective on deep imaging,

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-07T11:34:13.405595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 00435c17-83d9-4484-8ee3-c4c765881492 · outbound

This paper cites an unresolved cited work.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:34:13.107831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fb3199fb-65a3-4382-aaa4-d694bb377690 · outbound

This paper cites Low-dose ct denoising via sinogram inner-structure transformer,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose ct denoising via sinogram inner-structure transformer,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:12.852222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:55.873656Z digest=sha256:2112979a5dc977739392b7b40802a48882871434c3817cb08dbc3488697f6a36

Observation 9094611d-3ed7-4ec0-bfc3-2e59582310c4 · outbound

This paper cites Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Sinogram denoising via attention residual dense convolutional neural network for low-dose computed tomography,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:12.587879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:55.982566Z digest=sha256:5ad7c8c4af0fe17420c5f97533b3629c06ef3a769e4d59e9a732e0cf35fd07e2

Observation ece9981b-1deb-4ca6-9cc1-fbf48235f29c · outbound

This paper cites Ct sinogram-consistency learning for metal-induced beam hardening correction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Ct sinogram-consistency learning for metal-induced beam hardening correction,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:12.302622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:56.122066Z digest=sha256:490c3159f59c0cc29f22380c8cc46d1f11b3ed6f3afb7fb446a092a0a4fbe053

Observation da1e8cbd-eeb6-4184-a1e5-06ba93b42e4f · outbound

This paper cites Deep learning based sinogram correction for metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Deep learning based sinogram correction for metal artifact reduction,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:12.038262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:56.289081Z digest=sha256:048334434e6a50691a4691616973f5a9d49f488d276f9b5832698cad44252d3a

Observation f4796b07-1ae6-40db-a9d7-614471e2a122 · outbound

This paper cites Fast enhanced ct metal artifact reduction using data domain deep learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Fast enhanced ct metal artifact reduction using data domain deep learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:11.804367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:56.459332Z digest=sha256:6e0584c2d0e7e5567d0f90209eb23014accd34073621fb4539b1a3b5e71b916c

Observation 718dbb53-033c-46bf-8cbc-b83283f3f3d2 · outbound

This paper cites Low-dose CT via convolutional neural network,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose CT via convolutional neural network,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:11.504008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:56.599881Z digest=sha256:2aad850b3719fce306603551a4a34f113ee5aa5dd63bbe5cd626cdc64f8e7175

Observation a47e2b68-dc96-47cf-8d24-40a33d1214b8 · outbound

This paper cites Low-dose CT with a residual encoder-decoder convolutional neural network,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose CT with a residual encoder-decoder convolutional neural network,

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:56.728599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:56.728599Z digest=sha256:7b9df5bb337172cfb0c332d933423c005f54ec5035612e38f6ee19b59e5d4458

Observation ed0ba711-1554-43a0-a7c5-147bc2f2dfdd · outbound

This paper cites Deep con- volutional neural network for inverse problems in imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Deep con- volutional neural network for inverse problems in imaging,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:56.846856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:56.846856Z digest=sha256:ab1b0bcae7ed2aa045b06c3b99657330faa93acefb71f5ae17dce89966414de0

Observation 49b86f13-a7e3-4f72-b810-c3a7e9dcbd2b · outbound

This paper cites A deep convolutional neural network us- ing directional wavelets for low-dose X-ray CT reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A deep convolutional neural network us- ing directional wavelets for low-dose X-ray CT reconstruction,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:11.237666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:56.972966Z digest=sha256:5572d7f3f074226fd3dc902a6a635212f822d54cbb71c6366b7e9abc5e5b0906

Observation ff179c50-c0af-48cf-ab37-a69b6cf60b6a · outbound

This paper cites Low-dose CT image denoising using a generative adversarial network with wasserstein distance and perceptual loss,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dose CT image denoising using a generative adversarial network with wasserstein distance and perceptual loss,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:10.958200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.095149Z digest=sha256:1b86c4eeac81e2837e9f3917e858e49e68fca08fe9c61b6ac9da72e6c588354b

Observation 0af0b0fe-86c9-4b2d-a1b7-2b19eb2f2a49 · outbound

This paper cites Noise suppression with similarity-based self-supervised deep learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Noise suppression with similarity-based self-supervised deep learning,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:57.228409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:57.228409Z digest=sha256:9730b1c5d0998986217b9d51104ba958171adee25f4d54502bf401258a1bdc12

Observation fe53f710-058f-4dc3-a162-339dd035d911 · outbound

This paper cites Adn: artifact disen- tanglement network for unsupervised metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Adn: artifact disen- tanglement network for unsupervised metal artifact reduction,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:10.712273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.364272Z digest=sha256:e0426bb69d70082984c3cfbdfa4937892337f237e4eddaf08a822cfdf3b5b816

Observation a17d559e-a6e0-4326-9e2c-1659363aa4e4 · outbound

This paper cites Dicdnet: deep interpretable convolutional dictionary network for metal artifact reduction in ct images,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Dicdnet: deep interpretable convolutional dictionary network for metal artifact reduction in ct images,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:10.462259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.500632Z digest=sha256:c08000558d6b0b8234feaee804065f4fd676b61e7433b58c75dcf92b99f4bbf7

Observation 1cceebee-5376-4778-9254-20ad30d3bdde · outbound

This paper cites Low-dimensional manifold-constrained disentanglement network for metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-dimensional manifold-constrained disentanglement network for metal artifact reduction,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:10.294034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.622372Z digest=sha256:0df6fc45599d24ae4dfc8fedf1b73113683d092a9229a82a2a99f2aad1e3c80a

Observation 58dc741f-2597-43a2-9e31-5d35805fc30f · outbound

This paper cites Metal artifact reduction in 2d ct images with self-supervised cross-domain learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Metal artifact reduction in 2d ct images with self-supervised cross-domain learning,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:10.064871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.723552Z digest=sha256:a9d17861512acb5fc2d5e3e5ae23c8d0cc2930cf3544a7668358241692e1f7da

Observation bc79856d-3410-4d1c-a9af-4a77b65cea50 · outbound

This paper cites LEARN: Learned experts’ assessment- based reconstruction network for sparse-data CT,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine LEARN: Learned experts’ assessment- based reconstruction network for sparse-data CT,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:09.883221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:57.893063Z digest=sha256:3e682c2519f9390e79b70cd0fdf3d8446d9131e1b1f0215b9f4558a9a709e5bb

Observation 8a4ed96b-a6e6-43f6-9068-91d6bfe09583 · outbound

This paper cites CNN-based projected gradient descent for consistent CT image reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine CNN-based projected gradient descent for consistent CT image reconstruction,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:09.653885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.018544Z digest=sha256:dee4dbb50c4a14ad79c80e4ec15224aaa7a3933964a5a63bd6b57f167cff87f1

Observation 451c81df-f2c4-414e-af9c-bbaac3a0cafa · outbound

This paper cites Optimizing a parameterized plug-and-play ADMM for iterative low-dose CT reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Optimizing a parameterized plug-and-play ADMM for iterative low-dose CT reconstruction,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:09.395218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.155254Z digest=sha256:cae5dcd9084efe92afe03e0d4732501d8dd2a59e15f174804d27353cdef6cf7e

Observation 76fa2ca4-79ef-416e-a0d6-492159c8fcfb · outbound

This paper cites Adaptive Convolutional Dictionary Network for CT Metal Artifact Reduction.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Adaptive Convolutional Dictionary Network for CT Metal Artifact Reduction

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:58.280461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:58.280461Z digest=sha256:409a6a3409409892c24cffc1d15e9a3702a144a53640d2ca496e029de1c8d7a7

Observation 6822221c-e85a-45ce-9c0f-d3676ba227be · outbound

This paper cites FISTA-net: Learning a fast iterative shrinkage thresholding network for inverse problems in imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine FISTA-net: Learning a fast iterative shrinkage thresholding network for inverse problems in imaging,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:09.190724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.437795Z digest=sha256:927a600c51d1175dcf83fae1f27f3e736aa03791224e88067a6a67cd69d8661a

Observation 3bcdfc2e-e988-4ed4-9c40-51cf3987ab64 · outbound

This paper cites MAGIC: Manifold and graph integrative convolutional network for low-dose CT reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine MAGIC: Manifold and graph integrative convolutional network for low-dose CT reconstruction,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:08.958071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.567347Z digest=sha256:0163e0303a8dc9ff34cb7ce851bfc03ba64c94fe80151a3668c018189eaa3e40

Observation 9f138f1b-6d4c-48c4-82c1-f66a4b130642 · outbound

This paper cites Regformer: A local– nonlocal regularization-based model for sparse-view ct reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Regformer: A local– nonlocal regularization-based model for sparse-view ct reconstruction,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:08.737747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.655517Z digest=sha256:cfd32a25860e2123d18330b5b45e79ed170c227a0f571fff890dbc1ccd0a1761

Observation 7cd9bd05-ab88-4e84-a70b-46f710b6777c · outbound

This paper cites Convolutional neural network based metal artifact reduction in x-ray computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Convolutional neural network based metal artifact reduction in x-ray computed tomography,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:08.476636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.810775Z digest=sha256:c1a6fa361bafaf0d0655cbf316db6d70f1e2ef45f1f34f2b590c05ee7f173dfe

Observation 0286f167-ff89-42cd-bde5-a36156be6583 · outbound

This paper cites A dual-stream deep convolutional network for reducing metal streak artifacts in ct images,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A dual-stream deep convolutional network for reducing metal streak artifacts in ct images,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:08.280796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:58.966476Z digest=sha256:dad734027114e6eaf8445fe66400af056aec95cbbc8149d63b06c112e8bf91ef

Observation 9065a4df-77c1-4f1d-80d6-bef25ed1221d · outbound

This paper cites Deep sinogram completion with image prior for metal artifact reduction in ct images,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Deep sinogram completion with image prior for metal artifact reduction in ct images,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:08.025001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.076453Z digest=sha256:9b4d26773896b3ef69f40948a712c8e925a9debaf35206f8905739b595757216

Observation dc375df2-17da-49e1-966e-88fd446a62dc · outbound

This paper cites Image reconstruction by domain-transform manifold learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Image reconstruction by domain-transform manifold learning,

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:59.188685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:59.188685Z digest=sha256:6492f445b1dc0a5d766ee4089e8b889fb01159f362285d150e70e0240c88c1b8

Observation 1ea3fe57-da8b-47f8-bde0-9b7359d2fd62 · outbound

This paper cites Radon inversion via deep learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Radon inversion via deep learning,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:07.799762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.323027Z digest=sha256:bb4bd05aaf7cfe07dd436c83ccca3b381d8916822a0c168e81885e8bc650ab6d

Observation 1566c420-0a55-4bad-9e0d-85ef935e9cec · outbound

This paper cites Downsampled imaging geometric modeling for accurate CT reconstruction via deep learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Downsampled imaging geometric modeling for accurate CT reconstruction via deep learning,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:07.555614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.396939Z digest=sha256:5b5a09e8ae454002f4af09e4c699864cc86ab1df3747b4593988cfef18043d77

Observation 00de75e2-2aad-441a-ac5f-20185b3ed8dd · outbound

This paper cites Hybrid-domain neural network processing for sparse-view CT reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Hybrid-domain neural network processing for sparse-view CT reconstruction,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:07.307681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.539840Z digest=sha256:466fc0acbe8a8026f08c152d96fd9a593ed5333f808c4b50e0e197398eeef800

Observation 684aea46-3fb1-481a-8bd7-40b8cb37f1f4 · outbound

This paper cites CLEAR: comprehensive learning enabled adversarial reconstruction for subtle structure enhanced low- dose CT imaging,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine CLEAR: comprehensive learning enabled adversarial reconstruction for subtle structure enhanced low- dose CT imaging,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:07.077293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.658143Z digest=sha256:a1072ccf799348d454b4ae86cc45ecb6fece7f8235bd7c85f7b2f160a175c1d5

Observation 37fafa91-d3fa-4677-8a5e-0f5116e0a582 · outbound

This paper cites Learning to reconstruct CT images from the vvbp-tensor,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Learning to reconstruct CT images from the vvbp-tensor,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:06.874436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:33:59.796235Z digest=sha256:23a7fb05250d04bdc487c188412538cba49204f26f530c05c9aa076de55147ca

Observation dc43ce96-bf71-4c92-ac3b-d1acbc0cbe75 · outbound

This paper cites Learned primal-dual reconstruction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Learned primal-dual reconstruction,

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T11:33:59.959787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:33:59.959787Z digest=sha256:a4afac83398789c0957d62c382b299f9dd2688cfa1a8868fe53c877c4af07594

Observation 6616934d-6dd6-4975-a63e-b7a8394ed4e4 · outbound

This paper cites Dudonet: Dual domain network for ct metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Dudonet: Dual domain network for ct metal artifact reduction,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:06.660569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.071392Z digest=sha256:07332ad7696069a489f018042f5193118c8d16e0cf914c7177af7e111f7d31dd

Observation 600a9cb4-f80a-488b-b5fa-89870c2c01b0 · outbound

This paper cites Idol-net: An interactive dual-domain parallel network for ct metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Idol-net: An interactive dual-domain parallel network for ct metal artifact reduction,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:06.440824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.194125Z digest=sha256:29236aecbad69668be34d2acd46b881e6482c4700e41bd6789bf3eafed437a04

Observation bba67ab7-1901-491b-9c07-5e290d2c299d · outbound

This paper cites Dan-net: Dual-domain adaptive-scaling non-local network for ct metal artifact reduction,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Dan-net: Dual-domain adaptive-scaling non-local network for ct metal artifact reduction,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:06.185808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.312755Z digest=sha256:2dc1692187e3cf8c7bb28f39837bacea28f4e5baef8c2ffb637fe1f02c32da3d

Observation 615d9ff9-976f-4496-b32d-dfa8dada80b2 · outbound

This paper cites Cyclegan denoising of ex- treme low-dose cardiac ct using wavelet-assisted noise disentanglement,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Cyclegan denoising of ex- treme low-dose cardiac ct using wavelet-assisted noise disentanglement,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:05.953838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.433570Z digest=sha256:e8fe8fdba35617cbb7730ccaae6d16416868c7c597ea345ef24515b89a31bfd1

Observation 57496a22-f76a-4acc-b80e-c1c287140de2 · outbound

This paper cites Denoising diffusion probabilistic models,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Denoising diffusion probabilistic models,

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:00.580780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:00.580780Z digest=sha256:9f1c2d32cecbdc4e740d866fe73edcbe0a2a8576195faa4f8d7b1a13adc3322f

Observation 0ab2b23f-2ebe-4f03-8f04-4572e75df742 · outbound

This paper cites Image super-resolution via iterative refinement,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Image super-resolution via iterative refinement,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:05.622976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.715378Z digest=sha256:90f08444a293f0ffbbad4f197a991874336cced9cc9eb8c6b7f998eadfd98d4e

Observation f802c65b-777b-44b7-ab0c-f9524d10c7a6 · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Diffusion models beat gans on image synthesis,

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:00.815855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:00.815855Z digest=sha256:0525a5799bbc5ebd6df2ae511b0fdfa9685311386be2951d6eaf683f6c962dba

Observation 9d615690-5909-47c5-8321-9831c8f1a699 · outbound

This paper cites A denoising diffusion probabilistic model for metal artifact reduction in ct,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A denoising diffusion probabilistic model for metal artifact reduction in ct,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:05.357184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:00.943981Z digest=sha256:ece004f22ae89ab5d0718071ca58afa9de0c562f08dbcd831a4d2a7924bdc51a

Observation aa11099c-7e94-4511-bbea-6c14e0c1fb4f · outbound

This paper cites Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20$\times$ Speedup.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20$\times$ Speedup

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.071291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.071291Z digest=sha256:525a8dd0b9ac98556fc7dc79ba3c4352692cc312a7f747f4802aeed7796c8d72

Observation ebae41ae-71ef-463e-b0b2-2490b04c722e · outbound

This paper cites Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction

Reference 77

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:34:03.667247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:01.233022Z digest=sha256:5ebb5132dfbc28f1d69ad7d4c1d7a284ecbec1518af63a7d247f509bcf95f4cd

Observation cbacad3e-ff45-4ce8-b1a9-d5649e414864 · outbound

This paper cites Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT

Reference 78

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:34:03.471627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:01.375861Z digest=sha256:0e1250439e56c795dc2292664bb18f00af52c66c1981a07422fc870626423670

Observation efe859ef-d8da-4dc4-a5f1-6c5e8a050308 · outbound

This paper cites Poisson flow generative models,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Poisson flow generative models,

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.508537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.508537Z digest=sha256:7acbc07438651d00ee0bd631e9bc52ac348f2060ff025f2574c5ad95ea2f8c22

Observation 1d087e58-6d9a-4dfd-b7a8-68c537497860 · outbound

This paper cites Pfgm++: Unlocking the potential of physics-inspired generative models,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Pfgm++: Unlocking the potential of physics-inspired generative models,

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.622064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.622064Z digest=sha256:38e2cfb30670d1c9add9b063f626b5a7be4fe4251207f75a8bb6eda05d604c1f

Observation f38d71c5-a2eb-4e32-88bb-4b18736a5e36 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Score-Based Generative Modeling through Stochastic Differential Equations

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.753399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.753399Z digest=sha256:8518ae609d5c809b947fe277be139d7b15dbbc569f5bf9bdf7542e560eaf1ead

Observation d5740076-431e-4ad9-bd92-d048178969a9 · outbound

This paper cites Elucidating the design space of diffusion-based generative models,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Elucidating the design space of diffusion-based generative models,

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.865476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.865476Z digest=sha256:629a5ac82c72359f6fc5727310f0c7ed854c93e43caa67cc87bd6689be9cf6c8

Observation b34e13c8-784a-4fd7-b2e0-9759032433b6 · outbound

This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:01.968130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:01.968130Z digest=sha256:b75ad64a3b562af0393618120360c7be9292a86af05903246fb3b1ceeb2d2f40

Observation 556ab699-0ae5-4ade-a7a9-ad6dbaf57be7 · outbound

This paper cites Improving diffusion models for inverse problems using manifold constraints,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Improving diffusion models for inverse problems using manifold constraints,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:05.092943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:02.106785Z digest=sha256:66b52d586689f38680d06c07d62e690dfb71ffaddca5b28b1af3440e578a2ce1

Observation 2f9d3447-ad66-4a18-b46e-41c38036946e · outbound

This paper cites The little engine that could: Regularization by denoising (red),.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine The little engine that could: Regularization by denoising (red),

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:04.864632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:02.216283Z digest=sha256:7cb65106b109152410099ab2aaafc1cb6cf78cf1be87a0c2ae740757adfc7362

Observation 665b1afc-1bd6-42ef-9382-4efc3be525bc · outbound

This paper cites Ordered-subset simultaneous algebraic re- construction techniques (OS-SART),.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Ordered-subset simultaneous algebraic re- construction techniques (OS-SART),

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:04.678924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:02.359030Z digest=sha256:cf2dec4ad4c3482844e1708b039870cf34b7fa386c3207a3a38d7173a34a3226

Observation 929867b6-8a74-4bdf-a38a-0eb2fc10f983 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:02.489112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:02.489112Z digest=sha256:e587e14d41bb3643a7bf4c181f084c94aafa0f8da1671f483a5711e65acd4ae6

Observation 1362addb-d334-4e06-8d69-382ebe822594 · outbound

This paper cites Neural discrete representation learning,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Neural discrete representation learning,

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:02.618401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:02.618401Z digest=sha256:842fa9e8a741f077797489a924641d671f4e69e71540c5f897cd82d1d5baa1fe

Observation e47453f7-2fdc-4edb-91cc-3ceaef507b26 · outbound

This paper cites In-context learning unlocked for diffusion models,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine In-context learning unlocked for diffusion models,

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:02.766439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:02.766439Z digest=sha256:33c5542d4b6014cb2bc3c12712ec0433bf40fa2f71d16d58b256ff08dc13340d

Observation c62d018a-9cf4-4368-b7d8-bffd7e730ec2 · outbound

This paper cites SegGPT: Segmenting Everything In Context.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine SegGPT: Segmenting Everything In Context

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T11:34:02.883035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:34:02.883035Z digest=sha256:440af0d4bad1cbac2c1b94efffee967a2eaba4a29b811c8d637750032f4ab580

Observation ea79af38-0d8f-4584-acb9-228491cd848c · outbound

This paper cites Catsim: a new computer assisted tomography simulation environment,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Catsim: a new computer assisted tomography simulation environment,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:04.386569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:02.987873Z digest=sha256:efb7945229ad36c2f907c239b664bb6489fa529b125ae4df0ed81010b136d5c8

Observation 7bcf8d73-d86f-4aac-8f5f-e1ef0899b30b · outbound

This paper cites Dukesim: a realistic, rapid, and scanner-specific simulation framework in computed tomography,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine Dukesim: a realistic, rapid, and scanner-specific simulation framework in computed tomography,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:04.189985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:03.095408Z digest=sha256:9965271ec92069e1b7f36296557a0713b4a80d3bf57c93eda5f38fe9715852f8

Observation 88c36e77-772c-4de5-babe-e2c82fc3d4f1 · outbound

This paper cites A gpu tool for efficient, accurate, and realistic simulation of cone beam ct projections,.

Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine A gpu tool for efficient, accurate, and realistic simulation of cone beam ct projections,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:34:03.910397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:34:03.195506Z digest=sha256:49dde80a541fa36dfac81bb3ec36dd36bc0d91f82e01187122b25139f93db909

Pith citing papers

Observation 5a6415ab-6119-4869-b3f2-998ac21e7a3a · inbound

FORCE-Interior: A Poisson Flow Generative Prior for Interior Tomography Reconstruction cites this paper.

FORCE-Interior: A Poisson Flow Generative Prior for Interior Tomography Reconstruction Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T02:30:40.372846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:30:40.372846Z digest=sha256:25060a51bdb4ee6db876ea53418e8e037357e9556636119102828625c50d217a