Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction | Paper Citation Record

Observation f218c89b-888a-47b8-8dc2-a933dc722447 · outbound

This paper cites Automated brain tumor detection and segmentation for treatment response assessment using amino acid PET,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Automated brain tumor detection and segmentation for treatment response assessment using amino acid PET,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:45.274931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6b563f31-cd7d-43e0-9a16-c4b9aeabd258 · outbound

This paper cites PET imaging of neuroinflammation in neurological disorders,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction PET imaging of neuroinflammation in neurological disorders,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:45.046597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ac55841-a180-4b2c-b8fd-a588c5ca115a · outbound

This paper cites The basic principles of FDG-PET/CT imaging,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction The basic principles of FDG-PET/CT imaging,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:44.833816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cbbaf3e8-fb2b-4e1b-b700-9e31ad13659c · outbound

This paper cites Petformer netw ork enables ultra-low-dose tota l-body PET imaging without structural prior,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Petformer netw ork enables ultra-low-dose tota l-body PET imaging without structural prior,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:44.642883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 350b06a4-4faa-4542-aafc-25f8484654c7 · outbound

This paper cites Fast anisotropic gauss filtering,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Fast anisotropic gauss filtering,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:44.363004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8bed0505-8737-49da-86f8-1ccdefa57c6f · outbound

This paper cites Low dose PET reconstructio n with total variation regularization,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Low dose PET reconstructio n with total variation regularization,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:44.170992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c80786ed-d1da-4871-be50-2df7dd53ded1 · outbound

This paper cites Low dose PET image reconstruction 10 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. xx, NO. x, 2025 with total variation using alternating direction method,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Low dose PET image reconstruction 10 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. xx, NO. x, 2025 with total variation using alternating direction method,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:43.934466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4836bc2a-65f0-4012-8ba4-e642ca776dc9 · outbound

This paper cites Non-lo cal means denoising of dynamic PET images,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Non-lo cal means denoising of dynamic PET images,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:43.672844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2dc400bc-b730-4360-b851-e024e5d06be1 · outbound

This paper cites Spatially guided nonlocal mean approach f o r denoising of PET images,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Spatially guided nonlocal mean approach f o r denoising of PET images,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:43.377826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 54dc51c2-c0b1-4e3e-b1e9-3ee419726147 · outbound

This paper cites Image denoi sing with block-matching and 3d filtering,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Image denoi sing with block-matching and 3d filtering,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:43.063771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ad8e881f-8638-441b-824f-95f8f7ae1135 · outbound

This paper cites Anatomically guided PET image reconstruction using cond itional weakly-supervised multi- task learning integrati ng self-attention,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Anatomically guided PET image reconstruction using cond itional weakly-supervised multi- task learning integrati ng self-attention,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:42.805472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation efb27156-d6ff-4daa-bd31-95fc672349b7 · outbound

This paper cites Deep generalized learning model fo r PET image reconstruction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Deep generalized learning model fo r PET image reconstruction,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:42.606092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a43727cc-c818-41d6-bab6-2933e6505350 · outbound

This paper cites 200x Low-dose PET Reconstruction using Deep Learning.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction 200x Low-dose PET Reconstruction using Deep Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:31.927882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cbf22d5-8f9b-4076-afea-3b5485d12905 · outbound

This paper cites Multi-stage progressive image restoration,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Multi-stage progressive image restoration,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:42.396158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d9a459bc-7234-4b37-878b-d523f04ef19e · outbound

This paper cites Preliminary deep learning-based low dose whole body PET denoising incorpora ting CT information,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Preliminary deep learning-based low dose whole body PET denoising incorpora ting CT information,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:42.166967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aa78f614-6e9e-4322-9ba1-d43787f8a29c · outbound

This paper cites A total-body ultralow-dose PET r econstruction method via image space shuffle u-net and body sampling,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction A total-body ultralow-dose PET r econstruction method via image space shuffle u-net and body sampling,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:41.897489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9ec8bf8-5449-42e2-9d92-307b46533380 · outbound

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

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:32.437992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a64d16d6-f464-4ed8-940a-6705c4866689 · outbound

This paper cites Iterative PET image reconstruction using convolutional neural network representation,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Iterative PET image reconstruction using convolutional neural network representation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:41.694662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ec5b5b2b-9616-4db1-aeca-3bd57f6ea005 · outbound

This paper cites Ultra-low-dose PET reconstruction using generativ e adversarial network with fe ature matching and task-specific perceptual loss,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Ultra-low-dose PET reconstruction using generativ e adversarial network with fe ature matching and task-specific perceptual loss,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:41.505972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39658a9d-15b4-44d8-8fc7-c908327a5273 · outbound

This paper cites Generative adversarial networks,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Generative adversarial networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:41.259076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4dd4c75f-1b95-4635-9af8-25599da6be52 · outbound

This paper cites Wasserstein generativ e ad- versarial networks,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Wasserstein generativ e ad- versarial networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:41.078614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 34297747-e167-4679-a0fe-8ea8b64fe2e3 · outbound

This paper cites Improved training of wasserstein gans,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Improved training of wasserstein gans,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:40.770552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0a729b26-df11-477f-abcb-2e5eaea74e40 · outbound

This paper cites 3d multi- modality transformer-gan for high-quality PET reconstruction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction 3d multi- modality transformer-gan for high-quality PET reconstruction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:40.518569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation df7cae5a-6dd6-4e60-8dde-61483739c60c · outbound

This paper cites Prior knowledge-guided triple-domain transformer-gan for direct PET reconstruction from low-count sinograms,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Prior knowledge-guided triple-domain transformer-gan for direct PET reconstruction from low-count sinograms,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:40.322988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a3bdefa1-b68d-48f1-810e-579a46d6a863 · outbound

This paper cites Diffusion transf ormer model with compact prior for low-dose PET reconstruction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Diffusion transf ormer model with compact prior for low-dose PET reconstruction,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:40.061811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ba446bfa-1ff4-4cad-a27b-cc12644b87ec · outbound

This paper cites Bidirectiona l condition diffusion probabilistic models for PET image denoising,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Bidirectiona l condition diffusion probabilistic models for PET image denoising,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:39.805489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f4e76f52-3008-4c2b-824d-40746da1a04f · outbound

This paper cites PET imag e denoising based on denoising di ffusion probabilistic model,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction PET imag e denoising based on denoising di ffusion probabilistic model,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:39.625624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 84117d70-f6a2-4e7d-92e7-3a1b0244eee6 · outbound

This paper cites Denoising diffusion probabilistic models,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Denoising diffusion probabilistic models,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:33.698058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32ffe4cb-8ce7-437a-bdb1-95d9049cc749 · outbound

This paper cites Denoising Diffusion Implicit Models.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Denoising Diffusion Implicit Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:33.798430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 542ca9b6-d0d0-4f15-9ba3-9c5774dad621 · outbound

This paper cites Improved denoising diffusion probabilistic models,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Improved denoising diffusion probabilistic models,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:39.476240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7a64ffbd-febb-4cc3-8c06-9fcf287ead4a · outbound

This paper cites PET-diffusion: Unsupervised PET enhancement based on the latent diffusion model,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction PET-diffusion: Unsupervised PET enhancement based on the latent diffusion model,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:39.208107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fc31ad58-12c5-462f-9c32-28fa31a4b857 · outbound

This paper cites Contrastive diffusion model with auxiliary guidance for coarse-to-fine PET reconstruction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Contrastive diffusion model with auxiliary guidance for coarse-to-fine PET reconstruction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:38.948002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f5dd017-a4e2-4dd7-a671-a6369adce513 · outbound

This paper cites Brain PET Synthesis from MRI Using Joint Probability Distribution of Diffusion Model at Ultrahigh Fields.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Brain PET Synthesis from MRI Using Joint Probability Distribution of Diffusion Model at Ultrahigh Fields

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:43:36.063911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 97743275-dc93-45f1-b70f-0597b680d515 · outbound

This paper cites Synthesizing PET images from high-field and ultra-high-field MR images using joint diffusion attention model,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Synthesizing PET images from high-field and ultra-high-field MR images using joint diffusion attention model,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:38.704881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8f04ad7-e830-4e84-88af-17a2fd3f3c16 · outbound

This paper cites Joint diffusion: mutual consistency-dr iven diffusion model for PET-MR I co- reconstruction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Joint diffusion: mutual consistency-dr iven diffusion model for PET-MR I co- reconstruction,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:38.480231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1d24acb0-7a70-4b61-9780-404ee48fa32d · outbound

This paper cites Full- dose whole-body PET synthesis from low-dose PET using high-efficiency denoising diffusion probabilistic model: PET consistency model,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Full- dose whole-body PET synthesis from low-dose PET using high-efficiency denoising diffusion probabilistic model: PET consistency model,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:38.265020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 59c50919-59ff-4c29-8146-e42f8a9fae54 · outbound

This paper cites Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:34.692701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1638009a-4013-4121-96da-e6a9b302d87f · outbound

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

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Image super-resolution via iterative refinement,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:38.010015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a3137415-e71d-43fe-8066-301121c13d2e · outbound

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

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Diffusion models beat GANs on image synthesis,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:37.798512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 30e4fdc4-701d-4e23-b6e9-be5dc72f392f · outbound

This paper cites Ma sked autoencoders are scalable vision learners,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Ma sked autoencoders are scalable vision learners,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:37.584489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c62aea81-1c07-4c83-b9fc-9a677ca56d6d · outbound

This paper cites End-to-end object detection with transformers,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction End-to-end object detection with transformers,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:37.284086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9a41dcf-7426-4913-8ec2-79e7c744f72f · outbound

This paper cites White-box transformers via sparse rate reduction,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction White-box transformers via sparse rate reduction,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:37.041696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1857a7f7-ec1b-4f27-ab88-bc96f58aed8e · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction U-net: Convolutional networks for biomedical image segmentation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:36.811549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c4e9f1b7-c20e-4ee1-a4ce-68e8e73f1eae · outbound

This paper cites Image-to-image translation with conditional adversarial networks,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Image-to-image translation with conditional adversarial networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:36.604154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bad95925-894a-4f70-a4d2-7f511d7b4567 · outbound

This paper cites Adding conditional control to text- to-image diffusion models,.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Adding conditional control to text- to-image diffusion models,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:43:36.366855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation afacd7c6-1bf7-44eb-a034-0ba79d5d9023 · outbound

This paper cites Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration.

Double-Constraint Diffusion Model with Nuclear Regularization for Ultra-low-dose PET Reconstruction Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T13:43:35.755271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers