Paper Citation Record · LEDGER

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction

As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.15610.

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

pith.paper-citation-record.v1
2501.15610 v1

Coverage vector

measured 37 of 37 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation f0a8d001-bbb2-4abb-a223-efc328d534a2 · outbound

This paper cites CT dose reduction and dose management tools: overview of available options,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction CT dose reduction and dose management tools: overview of available options,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.153513Z

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Observation f3567545-1891-40b3-9688-33b0f07f7c47 · outbound

This paper cites Metal artifact reduction in CT: where are we after four decades?.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Metal artifact reduction in CT: where are we after four decades?

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.140955Z

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Observation 9fcf1d47-8f75-4e1b-a21c-fa9cd3e8bbe1 · outbound

This paper cites Tolerance levels for quality assurance of electron density values generated from CT in radiotherapy treatment planning,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Tolerance levels for quality assurance of electron density values generated from CT in radiotherapy treatment planning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.128613Z

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Observation 6322d563-1527-45c2-a699-5306c3750f13 · outbound

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

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Reduction of CT artifacts caused by metallic implants

Reference 4

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Observation d5d7d959-c10f-464d-901e-e68801f0f91c · outbound

This paper cites Nor- malized metal artifact reduction (NMAR) in computed tomography,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Nor- malized metal artifact reduction (NMAR) in computed tomography,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.103276Z

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Observation ad01657a-05d9-422c-8fe6-8129770e3131 · outbound

This paper cites Deep learning for tomographic image reconstruction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Deep learning for tomographic image reconstruction,

Reference 6

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Observation 892b5363-cbde-4805-8707-7c330437ff17 · outbound

This paper cites DuDoNet: Dual domain network for CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction DuDoNet: Dual domain network for CT metal artifact reduction,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.083505Z

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Observation 09f39acf-db1c-4fec-848a-13e595d50eb6 · outbound

This paper cites Dual domain diffusion guidance for 3D CBCT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Dual domain diffusion guidance for 3D CBCT metal artifact reduction,

Reference 8

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Observation 98deda6b-9e19-4750-b2e2-8bb80c565696 · outbound

This paper cites Quad-Net: Quad-domain network for CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Quad-Net: Quad-domain network for CT metal artifact reduction,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.060313Z

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Observation 3c887dfb-fc6e-4939-90e6-a1e7d4dade93 · outbound

This paper cites ADN: Artifact disentan- glement network for unsupervised metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction ADN: Artifact disentan- glement network for unsupervised metal artifact reduction,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.048411Z

Source-reported events for the cited work

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Observation 27a0d526-d961-4016-a408-46ed397dc939 · outbound

This paper cites Dense transformer based enhanced coding network for unsupervised metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Dense transformer based enhanced coding network for unsupervised metal artifact reduction,

Reference 11

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Observation 29b826f6-1169-479b-84a5-d1b7dea3bd47 · outbound

This paper cites Investigation of domain gap problem in several deep-learning-based CT metal artefact reduction methods.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Investigation of domain gap problem in several deep-learning-based CT metal artefact reduction methods

Reference 12

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Observation 92d16c9e-9b68-4bbd-a615-13aadcb8977b · outbound

This paper cites Unsupervised CT metal artifact learning us- ing attention-guided β-CycleGAN,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Unsupervised CT metal artifact learning us- ing attention-guided β-CycleGAN,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:43.022988Z

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Observation c18e34a2-c60e-487b-b779-86c438b4a45e · outbound

This paper cites Building a bridge: Close the domain gap in CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Building a bridge: Close the domain gap in CT metal artifact reduction,

Reference 14

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Observation fe8660d9-30de-4537-88aa-cfe77bc08001 · outbound

This paper cites Unsupervised CT metal artifact reduction by plugging diffusion priors in dual domains,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Unsupervised CT metal artifact reduction by plugging diffusion priors in dual domains,

Reference 15

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Observation e7df2ebf-5da9-498b-80b9-3820de6607d2 · outbound

This paper cites IDOL-Net: An interactive dual-domain parallel network for CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction IDOL-Net: An interactive dual-domain parallel network for CT metal artifact reduction,

Reference 16

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Observation cf7fcd6c-d7a0-47c7-beb4-461ab5d1d63f · outbound

This paper cites Wasserstein generative ad- versarial networks,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Wasserstein generative ad- versarial networks,

Reference 17

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Observation c99c244d-abd4-4a69-adf5-512721d1c6d0 · outbound

This paper cites The unusual effectiveness of averaging in GAN training,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction The unusual effectiveness of averaging in GAN training,

Reference 18

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Observation 134c6632-5caf-421a-9a8a-0760b4499dbf · outbound

This paper cites U-DuDoNet: Unpaired dual- domain network for CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction U-DuDoNet: Unpaired dual- domain network for CT metal artifact reduction,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.956731Z

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Observation d586abe2-fea9-40ee-b92d-7fe5c4da7e9e · outbound

This paper cites Deep- learning-based metal artefact reduction with unsupervised domain adap- tation regularization for practical CT images,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Deep- learning-based metal artefact reduction with unsupervised domain adap- tation regularization for practical CT images,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.945516Z

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Observation 3f90bbc8-b912-4ab1-bfd8-9d7c859afbc2 · outbound

This paper cites SemiMAR: Semi-supervised learning for CT metal artifact reduction,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction SemiMAR: Semi-supervised learning for CT metal artifact reduction,

Reference 21

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Observation 1e644ccf-9396-4e16-b804-a6f171595cb9 · outbound

This paper cites Domain-adversarial training of neural networks,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Domain-adversarial training of neural networks,

Reference 22

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Observation 34c88a97-9df3-4806-b7cb-b0498a876564 · outbound

This paper cites Pseudo-labeling and confirmation bias in deep semi-supervised learn- ing,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Pseudo-labeling and confirmation bias in deep semi-supervised learn- ing,

Reference 23

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Observation 3e24f114-9b09-4c12-9727-6effc66f32ee · outbound

This paper cites mixup: Beyond empirical risk minimization,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction mixup: Beyond empirical risk minimization,

Reference 24

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Observation f068bc4d-3dc6-4ac5-8864-6e85245c574b · outbound

This paper cites Prompted Contextual Transformer for Incomplete-View CT Reconstruction.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Prompted Contextual Transformer for Incomplete-View CT Reconstruction

Reference 25

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This paper cites Swin Transformer: Hierarchical vision transformer using shifted win- dows,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Swin Transformer: Hierarchical vision transformer using shifted win- dows,

Reference 26

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Observation 5f07785d-cdf2-4936-bb4f-e1a391fb9723 · outbound

This paper cites Learning to distill global representation for sparse-view CT,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Learning to distill global representation for sparse-view CT,

Reference 27

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Observation 653604ff-0d45-453a-a7df-a6c94555891a · outbound

This paper cites DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning,

Reference 28

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Observation 26dcfb82-df9d-4e6f-b543-25fab743aecc · outbound

This paper cites Deep learning to segment pelvic bones: large-scale CT datasets and baseline models,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Deep learning to segment pelvic bones: large-scale CT datasets and baseline models,

Reference 29

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Observation fddacf06-3aa2-4614-a9f8-af44e75f4b5e · outbound

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

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Convolutional neural network based metal artifact reduction in x-ray computed tomography,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.841151Z

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Observation a355eadd-0c30-4587-b3f2-8e6a3943d7ac · outbound

This paper cites Unpaired image-to- image translation using cycle-consistent adversarial networks,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Unpaired image-to- image translation using cycle-consistent adversarial networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.829480Z

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Observation f97ff84a-09f1-4619-bd17-97beb7e67df7 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Image quality assessment: from error visibility to structural similarity,

Reference 32

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Observation 9ea93a3e-8497-46f9-a665-c42343856eb5 · outbound

This paper cites IQA- GPT: Computed tomography image quality assessment with vision- language and ChatGPT models,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction IQA- GPT: Computed tomography image quality assessment with vision- language and ChatGPT models,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.809994Z

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Observation 57537ce6-95ea-4b9d-a39b-4c17a1400f3c · outbound

This paper cites Rich human feedback for text-to-image generation,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Rich human feedback for text-to-image generation,

Reference 34

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Observation 61563d46-9b32-4f2a-bb98-cf1a02befca8 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Very deep convolutional networks for large-scale image recognition,

Reference 35

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Observation 0f98c2e7-80b1-458a-ac2d-2e312f777564 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Learning transferable visual models from natural language supervision,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.773563Z

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Observation bd2c517d-5223-46f2-9da1-c9583fc46429 · outbound

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

Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction Perceptual losses for real-time style transfer and super-resolution,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:09:42.762016Z

Source-reported events for the cited work

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Pith citing papers

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