Paper Citation Record · LEDGER

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction

As of 14 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2607.16491.

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

pith.paper-citation-record.v1
2607.16491 v1

Coverage vector

measured 48 of 48 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T20:54:16.839755Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

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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

48 of 48 outbound references displayed

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External citation measurements

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Outbound references

Observation ac4a54ae-1b6f-4df2-b121-1e4234f5801a · outbound

This paper cites Denoising diffusion probabilistic models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Denoising diffusion probabilistic models,

Reference 1

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Observation e9f3cf2c-be70-418f-bb23-4ab90602a250 · outbound

This paper cites Denoising diffusion probabilistic models for 3d medical image generation,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Denoising diffusion probabilistic models for 3d medical image generation,

Reference 2

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Observation 2839c5ab-b535-4a84-8f76-f20418489812 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction High-resolution image synthesis with latent diffusion models,

Reference 3

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Observation fb5f10eb-1f97-400c-9515-3c941faffa58 · outbound

This paper cites Brain imaging generation with latent diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Brain imaging generation with latent diffusion models,

Reference 4

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Observation 1aeb68ae-8597-4908-944d-b0d387d1f83b · outbound

This paper cites Memory-efficient 3d denoising diffusion models for medical image processing,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Memory-efficient 3d denoising diffusion models for medical image processing,

Reference 5

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Observation 2e88dac0-115c-4c23-b856-53a7e5f2dc59 · outbound

This paper cites Medsyn: Text- guided anatomy-aware synthesis of high-fidelity 3d ct images,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Medsyn: Text- guided anatomy-aware synthesis of high-fidelity 3d ct images,

Reference 6

Resolution: verified exact; doi, observed 2026-08-01T20:58:29.101950Z

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Observation 8692a3b4-919c-41bb-bb49-d8fb21d25df0 · outbound

This paper cites Anatomically guided latent diffusion for high-resolution 3d chest ct synthesis,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Anatomically guided latent diffusion for high-resolution 3d chest ct synthesis,

Reference 7

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Observation 768c3cea-ab52-4042-bd4a-e76e969df7fb · outbound

This paper cites Maisi: Medical ai for synthetic imaging,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Maisi: Medical ai for synthetic imaging,

Reference 8

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Observation b1f47e41-c366-4b42-acfa-233f6048b991 · outbound

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Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Unresolved cited work

Reference 9

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Observation f974a75c-2df1-4995-97f8-f845a6c14f70 · outbound

This paper cites 3d meddiffusion: A 3d medical latent diffusion model for controllable and high-quality medical image generation,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction 3d meddiffusion: A 3d medical latent diffusion model for controllable and high-quality medical image generation,

Reference 10

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Observation d8dbd6b7-bc44-4238-ab01-707a2ba124d7 · outbound

This paper cites Hierarchical amortized gan for 3d high resolution medical image synthesis,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Hierarchical amortized gan for 3d high resolution medical image synthesis,

Reference 11

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Observation 438aed9e-949d-4199-b412-fdae266165ee · outbound

This paper cites Learning image priors through patch-based diffusion models for solving inverse problems,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Learning image priors through patch-based diffusion models for solving inverse problems,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T20:54:14.171571Z

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Observation cae0243d-1551-4deb-b492-c3c58a0caa7e · outbound

This paper cites Diffusionblend: Learning 3d image prior through position-aware diffusion score blending for 3d computed tomography reconstruction,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Diffusionblend: Learning 3d image prior through position-aware diffusion score blending for 3d computed tomography reconstruction,

Reference 13

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Observation f963e573-8760-4518-b051-aa832d951c80 · outbound

This paper cites Nerp: Implicit neural representation learning with prior embedding for sparsely sampled image reconstruc- tion,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Nerp: Implicit neural representation learning with prior embedding for sparsely sampled image reconstruc- tion,

Reference 14

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Observation 7d338429-ae66-4393-b352-1192768a3f17 · outbound

This paper cites Im- jense: Scan-specific implicit representation for joint coil sensitivity and image estimation in parallel mri,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Im- jense: Scan-specific implicit representation for joint coil sensitivity and image estimation in parallel mri,

Reference 15

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Observation 3cfd4c2f-a119-4739-9824-f007b627c373 · outbound

This paper cites Scan-specific unsupervised highly accelerated non-cartesian cest imaging using implicit neural repre- sentation and explicit sparse prior,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Scan-specific unsupervised highly accelerated non-cartesian cest imaging using implicit neural repre- sentation and explicit sparse prior,

Reference 16

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Observation e912cc5c-996d-44bc-92fe-a0ce7160b7f2 · outbound

This paper cites Spatiotemporal implicit neural representation for unsupervised dynamic mri reconstruction,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Spatiotemporal implicit neural representation for unsupervised dynamic mri reconstruction,

Reference 17

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Observation 520abc6f-2d52-4d64-87f4-bf61c6f8b569 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 18

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Observation ad2a7398-5ce5-4ae9-9f35-b08fa4dfe422 · outbound

This paper cites Implicit neural representations with periodic activation functions,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Implicit neural representations with periodic activation functions,

Reference 19

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Observation bb7ee4a4-758c-4edf-801f-3d7c24db8a3b · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Instant neural graphics primitives with a multiresolution hash encoding,

Reference 20

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Observation d4e68d93-bb5b-4f11-b24a-097e795470e2 · outbound

This paper cites Bilevel optimized implicit neural representation for scan-specific accelerated mri reconstruction,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Bilevel optimized implicit neural representation for scan-specific accelerated mri reconstruction,

Reference 21

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Observation de1188e5-9fab-4d04-baa9-1ee3de99b5f9 · outbound

This paper cites Learning continuous image repre- sentation with local implicit image function,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Learning continuous image repre- sentation with local implicit image function,

Reference 22

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Observation 7f915650-3872-4e70-9a2e-37ac76046c1f · outbound

This paper cites Arbitrary-scale image generation and upsam- pling using latent diffusion model and implicit neural decoder,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Arbitrary-scale image generation and upsam- pling using latent diffusion model and implicit neural decoder,

Reference 23

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Observation 9c3ba65e-90f7-4d03-b56f-e49578d49c9e · outbound

This paper cites LoFi: Neural Local Fields for Scalable Image Reconstruction.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction LoFi: Neural Local Fields for Scalable Image Reconstruction

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-01T20:58:28.840232Z

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Observation 00244366-d2d6-4c40-bc95-9f86377610b3 · outbound

This paper cites Diff-INR: Generative Regularization for Electrical Impedance Tomography.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Diff-INR: Generative Regularization for Electrical Impedance Tomography

Reference 25

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Observation 96100474-7abc-41ac-9767-1e97348ec5b7 · outbound

This paper cites Highly accelerated mri via implicit neural representation guided posterior sampling of diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Highly accelerated mri via implicit neural representation guided posterior sampling of diffusion models,

Reference 26

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Observation 15644fab-0cb4-45f7-be58-5bda038ecb81 · outbound

This paper cites MedIL: Implicit Latent Spaces for Generating Heterogeneous Medical Images at Arbitrary Resolutions.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction MedIL: Implicit Latent Spaces for Generating Heterogeneous Medical Images at Arbitrary Resolutions

Reference 27

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Observation bdbf842e-1216-4137-a2e8-d0dae50a7d29 · outbound

This paper cites Diffusion Posterior Sampling for General Noisy Inverse Problems.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Diffusion Posterior Sampling for General Noisy Inverse Problems

Reference 28

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Observation e5a15c3a-d04a-42c6-bb92-5871fb54eae3 · outbound

This paper cites Solving inverse problems with latent diffusion models via hard data con- sistency,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Solving inverse problems with latent diffusion models via hard data con- sistency,

Reference 29

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Observation a86de2d5-2e63-4acd-80bc-f3161004e42f · outbound

This paper cites Denoising diffusion models for plug-and-play image restoration,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Denoising diffusion models for plug-and-play image restoration,

Reference 30

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Observation d27f3362-3450-49d8-8a00-b6bfe90fc0c2 · outbound

This paper cites Prompt-tuning latent diffusion models for inverse problems.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Prompt-tuning latent diffusion models for inverse problems

Reference 31

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Observation 161eb178-a627-45f7-a191-534f9e95b452 · outbound

This paper cites The lung image database consortium (lidc) and image database resource initiative (idri): A completed reference database of lung nodules on ct scans,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction The lung image database consortium (lidc) and image database resource initiative (idri): A completed reference database of lung nodules on ct scans,

Reference 32

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Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Unresolved cited work

Reference 33

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Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Unresolved cited work

Reference 34

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This paper cites Radimagenet: An open radiologic deep learning research dataset for effective transfer learning,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Radimagenet: An open radiologic deep learning research dataset for effective transfer learning,

Reference 35

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Observation e1ec6286-8f82-4f15-a2f0-2d7b08f7cadc · outbound

This paper cites TorchRadon: Fast Differentiable Routines for Computed Tomography.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction TorchRadon: Fast Differentiable Routines for Computed Tomography

Reference 36

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This paper cites Solving 3d inverse problems using pre-trained 2d diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Solving 3d inverse problems using pre-trained 2d diffusion models,

Reference 37

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This paper cites Improving 3d imaging with pre-trained perpendicular 2d diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Improving 3d imaging with pre-trained perpendicular 2d diffusion models,

Reference 38

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This paper cites Decomposed diffusion sampler for accelerating large-scale inverse problems,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Decomposed diffusion sampler for accelerating large-scale inverse problems,

Reference 39

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This paper cites Adaptive diffusion models for sparse-view motion-corrected head cone-beam ct,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Adaptive diffusion models for sparse-view motion-corrected head cone-beam ct,

Reference 40

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Observation 9f588db1-cfb9-49e6-9e40-901ad44e1b78 · outbound

This paper cites Improving 2d diffusion models for 3d medical imaging with inter-slice consistent stochasticity,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Improving 2d diffusion models for 3d medical imaging with inter-slice consistent stochasticity,

Reference 41

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Observation 19593872-8ac6-477b-9dc9-147db9846a6b · outbound

This paper cites Solving linear inverse problems provably via posterior sampling with latent diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Solving linear inverse problems provably via posterior sampling with latent diffusion models,

Reference 42

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Observation 682b8bb2-17f9-466e-899b-edc77194e25d · outbound

This paper cites Image neural field diffusion models,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Image neural field diffusion models,

Reference 43

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Observation 374b832b-3353-410e-93ff-f652eaf4dbcc · outbound

This paper cites Towards lossless implicit neural representation via bit plane decomposition,.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Towards lossless implicit neural representation via bit plane decomposition,

Reference 44

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Observation 99d0e0fa-4d9b-498f-b77d-990d907e1ccf · outbound

This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 45

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Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Sana-video: Efficient video generation with block linear diffusion transformer,

Reference 46

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Observation be623584-3288-4408-995c-a98d0ff75c47 · outbound

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Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Unresolved cited work

Reference 2015

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Observation e44e8f03-b715-473e-b08b-a97b6887c435 · outbound

This paper cites Diff-INR: Generative Regularization for Electrical Impedance Tomography.

Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction Diff-INR: Generative Regularization for Electrical Impedance Tomography

Reference 2024

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Pith citing papers

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