Paper Citation Record · LEDGER

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment

As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.20200.

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

pith.paper-citation-record.v1
2506.20200 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:58:05.854806Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy29
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1dea5894-1b7f-4735-8add-d00e0c4d1718 · outbound

This paper cites PET/CT imaging artifacts.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment PET/CT imaging artifacts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.234252Z

Source-reported events for the cited work

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Observation c333800c-e56c-49f1-a946-9d32ad3d3459 · outbound

This paper cites An artificial intelligence-driven image quality assessment system for whole-body [18F] FDG PET/CT.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment An artificial intelligence-driven image quality assessment system for whole-body [18F] FDG PET/CT

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.223764Z

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Observation 5e0fa06c-5b66-490c-ae3f-7fc71996778a · outbound

This paper cites Modern image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Modern image quality assessment

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.213084Z

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Observation 569af917-d983-4a55-8b24-00bc02368cde · outbound

This paper cites Review of medical image quality as- sessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Review of medical image quality as- sessment

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.203027Z

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Observation 6e19327a-328a-485b-89d1-2fb2f720b812 · outbound

This paper cites Making a “completely blind.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Making a “completely blind

Reference 5

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Observation 56b84a30-60be-46c4-befc-e53600eeee7a · outbound

This paper cites No-reference im- age quality assessment in the spatial domain.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment No-reference im- age quality assessment in the spatial domain

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.180809Z

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Observation f0e0d4e0-c6b0-4239-a1ec-cb01c48ec974 · outbound

This paper cites C-DIIVINE: No-reference image quality assessment based on local magnitude and phase statistics of natural scenes.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment C-DIIVINE: No-reference image quality assessment based on local magnitude and phase statistics of natural scenes

Reference 7

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Observation a539cb68-18a7-451d-baa1-a59d2e54cf87 · outbound

This paper cites Deep neural networks for no-reference and full-reference image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Deep neural networks for no-reference and full-reference image quality assessment

Reference 8

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Observation 2ce79461-1617-49eb-a626-6044c3bd9475 · outbound

This paper cites On the use of deep learning for blind image quality assess- ment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment On the use of deep learning for blind image quality assess- ment

Reference 9

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Source-reported events for the cited work

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Observation c6567efa-88c0-46d9-869e-f94728255379 · outbound

This paper cites On the use of deep learning for blind image quality assess- ment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment On the use of deep learning for blind image quality assess- ment

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.134045Z

Source-reported events for the cited work

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Observation f23ab445-b084-4112-8028-2d6ec9c27263 · outbound

This paper cites SSIQA: Multi-task learning for non-reference CT image quality assessment with self-supervised noise level predic- tion.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment SSIQA: Multi-task learning for non-reference CT image quality assessment with self-supervised noise level predic- tion

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.122628Z

Source-reported events for the cited work

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Observation 49865739-8905-4252-ad16-26840990ed4a · outbound

This paper cites Performance evaluation of image quality metrics for per- ceptual assessment of low-dose computed tomography images.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Performance evaluation of image quality metrics for per- ceptual assessment of low-dose computed tomography images

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.112226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e5f8baa7-ab05-44d0-91d4-9b0ae4db855b · outbound

This paper cites Gradient-based learning applied to document recognition.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Gradient-based learning applied to document recognition

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.090173Z

Source-reported events for the cited work

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Observation 8d14b551-c97a-4489-8507-611164180a93 · outbound

This paper cites Attention is all you need.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Attention is all you need

Reference 15

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Source-reported events for the cited work

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Observation 623f519a-351a-46dd-b420-0c9c6083bf75 · outbound

This paper cites No-reference image quality assessment via transformers, relative ranking, and self-consistency.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment No-reference image quality assessment via transformers, relative ranking, and self-consistency

Reference 16

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Observation 7cdd08da-8f61-46b1-a1cb-d047219a00fc · outbound

This paper cites Deep learning in medical image analysis.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Deep learning in medical image analysis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.063721Z

Source-reported events for the cited work

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Observation ce64992f-f54b-4343-a479-3448c0828d2d · outbound

This paper cites Deep learning-based feature representation for AD/MCI classification.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Deep learning-based feature representation for AD/MCI classification

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.053617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 80af4b97-6071-4535-a250-0b5643625a52 · outbound

This paper cites Low-dose computed tomography perceptual image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Low-dose computed tomography perceptual image quality assessment

Reference 19

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Observation 9b08ef1d-b1db-4f5f-90d7-a5834a803f5a · outbound

This paper cites Deep residual learning for image recognition.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Deep residual learning for image recognition

Reference 20

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Observation d3628b09-73f5-479e-a2f3-1eebb2dd78f5 · outbound

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

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Swin transformer: Hierarchical vision transformer using shifted win- dows

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.036318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7119e6d4-c4ac-4e78-8632-f00d68559cc2 · outbound

This paper cites AGCA: An adaptive graph channel attention module for steel surface defect detection.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment AGCA: An adaptive graph channel attention module for steel surface defect detection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.025843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3b35315d-6631-42d5-8b33-d46d4f4205cd · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 23

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Observation 6c97dd74-3577-46d2-961d-4b5157c15848 · outbound

This paper cites An empirical comparison of voting classification algorithms: Bagging, boosting, and variants.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment An empirical comparison of voting classification algorithms: Bagging, boosting, and variants

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:06.015075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8a4a5cbf-15d4-4b15-8c2d-7e5d9e500be8 · outbound

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MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ba523d1-dfa2-4e2a-b3c4-6a35b5de2564 · outbound

This paper cites Statistical image reconstruction for polyenergetic X-ray computed tomography.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Statistical image reconstruction for polyenergetic X-ray computed tomography

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.993256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3580c601-6288-48df-a7fa-f66979d423bc · outbound

This paper cites Blindlyassessimagequalityinthewildguidedbyaself-adaptive hyper network.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Blindlyassessimagequalityinthewildguidedbyaself-adaptive hyper network

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.982354Z

Source-reported events for the cited work

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Observation 0177a2b9-d38e-4a76-8120-ba6769da34e4 · outbound

This paper cites Musiq: Multi-scale image quality transformer.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Musiq: Multi-scale image quality transformer

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.972027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 620c5454-2eb8-478a-8270-d62c14ea29f3 · outbound

This paper cites Image quality assessment using contrastive learn- ing.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Image quality assessment using contrastive learn- ing

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.961221Z

Source-reported events for the cited work

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Observation 35c157db-8884-44f4-b783-172fc2824ee8 · outbound

This paper cites Maniqa: Multi-dimension attention network for no-reference image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Maniqa: Multi-dimension attention network for no-reference image quality assessment

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.949470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 84d63f2b-1d8a-4428-b311-4b684c4ff3f0 · outbound

This paper cites Topiq: A top-down approach from semantics to distortions for image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Topiq: A top-down approach from semantics to distortions for image quality assessment

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.938326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4ec46bae-0a34-4fa8-9205-61e6c863afda · outbound

This paper cites Re-iqa: Unsupervised learning for image quality assessment in the wild.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Re-iqa: Unsupervised learning for image quality assessment in the wild

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.926993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4d8d4f24-f2ea-4d6a-bae9-901707435124 · outbound

This paper cites Arniqa: Learning distortion manifold for image quality assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Arniqa: Learning distortion manifold for image quality assessment

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.916070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1e9075ed-051a-406a-86cd-bb52a9e654ed · outbound

This paper cites Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment

Reference 34

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Source-reported events for the cited work

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Observation 54b638a7-9976-4220-b758-9aff3e82107f · outbound

This paper cites Blind image quality assess- ment based on geometric order learning.

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment Blind image quality assess- ment based on geometric order learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:58:05.905072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.