Paper Citation Record · LEDGER

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models

As of 12 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2501.15248.

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

pith.paper-citation-record.v1
2501.15248 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:31:39.980189Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:36:39.661933Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:36:39.954323Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy27
unresolved9
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 49d589d8-c136-4903-ab5e-4eb1c2087a05 · outbound

This paper cites Automatic pulmonary nodule detection applying deep learning or machine learning algorithms to the lidc-idri database: a systematic review.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Automatic pulmonary nodule detection applying deep learning or machine learning algorithms to the lidc-idri database: a systematic review

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.511143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a3fe6220-c03c-49e1-b754-8ce07071795b · outbound

This paper cites Medical image segmentation using deep learning: A survey.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Medical image segmentation using deep learning: A survey

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.497318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a71afbdd-8673-4c57-85b5-80a7ec9bb99a · outbound

This paper cites A review of the application of deep learning in medical image classification and segmentation.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models A review of the application of deep learning in medical image classification and segmentation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.483701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5773a4f0-4d76-46de-ae3f-13924f67e048 · outbound

This paper cites Handwritten digit recognition with a back-propagation network.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Handwritten digit recognition with a back-propagation network

Reference 4

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Source-reported events for the cited work

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Observation 16222954-4c97-48bd-bd34-760839517c46 · outbound

This paper cites Deep residual learning for image recognition.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Deep residual learning for image recognition

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T14:31:39.848470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aec9269-4b63-4e3f-86b9-730431248688 · outbound

This paper cites Novel transfer learning approach for medical imaging with limited labeled data.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Novel transfer learning approach for medical imaging with limited labeled data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.449813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce912980-b92b-4f5b-8fd8-852c6a3ccde5 · outbound

This paper cites Dense prediction and local fusion of superpixels: A framework for breast anatomy segmentation in ultrasound image with scarce data.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Dense prediction and local fusion of superpixels: A framework for breast anatomy segmentation in ultrasound image with scarce data

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.434435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5894f686-787b-4fd9-b485-e426f4a37a42 · outbound

This paper cites Machine learning for medical ultrasound: status, methods, and future opportunities.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Machine learning for medical ultrasound: status, methods, and future opportunities

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.420493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7a28a93e-5d91-47ec-b1c1-63f830c313db · outbound

This paper cites u tte, J \.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models u tte, J \

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.406596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 66d68701-c92e-44a6-8422-c25e33cb8911 · outbound

This paper cites Generative adversarial nets.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Generative adversarial nets

Reference 10

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Source-reported events for the cited work

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Observation 927e45d0-323a-4481-afb2-4abe4bc0d064 · outbound

This paper cites Denoising diffusion probabilistic models.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Denoising diffusion probabilistic models

Reference 11

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Source-reported events for the cited work

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Observation 22bc8a08-4acc-44e4-818e-7d61d7d384aa · outbound

This paper cites Gan-based synthetic medical image augmentation for increased cnn performance in liver lesion classification.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Gan-based synthetic medical image augmentation for increased cnn performance in liver lesion classification

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.373268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb45eae0-d8c4-4b1a-ad01-9a85bedf88b8 · outbound

This paper cites Data augmentation using generative adversarial networks (gans) for gan-based detection of pneumonia and covid-19 in chest x-ray images.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Data augmentation using generative adversarial networks (gans) for gan-based detection of pneumonia and covid-19 in chest x-ray images

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.356972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b59310e0-9b56-442a-b0e0-ebdbcb88cc7a · outbound

This paper cites Generative adversarial network in medical imaging: A review.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Generative adversarial network in medical imaging: A review

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.342460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 16f160b4-23e4-4f7a-ac26-c712f7136364 · outbound

This paper cites 2d medical image synthesis using transformer-based denoising diffusion probabilistic model.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models 2d medical image synthesis using transformer-based denoising diffusion probabilistic model

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.328269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 51c4e921-64be-4dae-aa5b-2de903c8535b · outbound

This paper cites Improving nonalcoholic fatty liver disease classification performance with latent diffusion models.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Improving nonalcoholic fatty liver disease classification performance with latent diffusion models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.313416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e228cf47-3bcc-4f46-aca1-6e382c457bd8 · outbound

This paper cites Noise-consistent siamese-diffusion for medical image synthesis and segmentation.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Noise-consistent siamese-diffusion for medical image synthesis and segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.298114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e6e27512-a0da-4a17-8b8c-0078b6594061 · outbound

This paper cites On Convergence and Stability of GANs.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models On Convergence and Stability of GANs

Reference 18

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Source-reported events for the cited work

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Observation 1dcd7971-c463-488d-8d6a-6e64d4366d79 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Diffusion models beat gans on image synthesis

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T14:31:39.906162Z

Source-reported events for the cited work

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Observation 0a5b75af-49be-4838-82e9-627a2db5a997 · outbound

This paper cites Differential data augmentation techniques for medical imaging classification tasks.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Differential data augmentation techniques for medical imaging classification tasks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.271073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 606423c5-9870-4a44-abcd-3b0a371697a0 · outbound

This paper cites Medical image data augmentation: techniques, comparisons and interpretations.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Medical image data augmentation: techniques, comparisons and interpretations

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.257995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d26efd26-11f9-4e52-9ecc-ee41de20bf33 · outbound

This paper cites Data augmentation and transfer learning to improve generalizability of an automated prostate segmentation model.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Data augmentation and transfer learning to improve generalizability of an automated prostate segmentation model

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.243538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c7769b71-31d3-4484-a550-0b0d4c442e07 · outbound

This paper cites Generative adversarial networks to improve fetal brain fine-grained plane classification.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Generative adversarial networks to improve fetal brain fine-grained plane classification

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.230017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f1891295-f295-4fe6-8a64-eb2345e71cb4 · outbound

This paper cites Unified brain mr-ultrasound synthesis using multi-modal hierarchical representations.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Unified brain mr-ultrasound synthesis using multi-modal hierarchical representations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.215953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 552e5c3d-864f-45fd-ac47-93f409cdb3c1 · outbound

This paper cites Automated classification of common maternal fetal ultrasound planes using multi-layer perceptron with deep feature integration.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Automated classification of common maternal fetal ultrasound planes using multi-layer perceptron with deep feature integration

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.201634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 247db277-69a9-434a-8bdb-108bd12df066 · outbound

This paper cites Standard fetal ultrasound plane classification based on stacked ensemble of deep learning models.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Standard fetal ultrasound plane classification based on stacked ensemble of deep learning models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.187285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 857d2771-03a4-4045-8159-8da00cce767d · outbound

This paper cites Automated deep bottleneck residual 82-layered architecture with bayesian optimization for the classification of brain and common maternal fetal ultrasound planes.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Automated deep bottleneck residual 82-layered architecture with bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.172511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 41d8fa88-8a94-4e90-a514-a5b5bcbe47b6 · outbound

This paper cites Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.156692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 805098e7-52c1-495d-b55e-e76fe83adb8c · outbound

This paper cites Automatic identification of fetal biometry planes from ultrasound images: An assistive tool for healthcare professionals.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Automatic identification of fetal biometry planes from ultrasound images: An assistive tool for healthcare professionals

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.140273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1985b960-ac91-46e2-9827-88f42fb81dbf · outbound

This paper cites A deep convolutional neural network with adaptive channel weight technique for automated identification of standard fetal biometry planes.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models A deep convolutional neural network with adaptive channel weight technique for automated identification of standard fetal biometry planes

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.125247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation abebbb90-9b0b-4523-96b4-7b7f21b78252 · outbound

This paper cites Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.110817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1540b182-141c-4a31-80a4-f3cc22601e6c · outbound

This paper cites Densely connected convolutional networks.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Densely connected convolutional networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.094249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b0a31be9-491b-4755-81ae-2559f43168e4 · outbound

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

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 33

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Source-reported events for the cited work

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Observation 7ca2541a-9c2d-4c09-be43-352cc1b1fc50 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:31:40.079277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b9a78bcb-e6dc-4701-892f-871c77c85b18 · outbound

This paper cites MedMamba: Vision Mamba for Medical Image Classification.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models MedMamba: Vision Mamba for Medical Image Classification

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T14:31:39.975301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dc77f7e-7bc9-443a-87fa-57139d0f33a2 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models Adam: A Method for Stochastic Optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T14:31:39.980189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c3890804-5a76-48ac-97fc-aa1e8af5d486 · inbound

Adaptively Distilled ControlNet: Accelerated Training and Superior Sampling for Medical Image Synthesis cites this paper.

Adaptively Distilled ControlNet: Accelerated Training and Superior Sampling for Medical Image Synthesis Enhancing Fetal Plane Classification Accuracy with Data Augmentation Using Diffusion Models

Reference 30

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T10:36:39.973344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.