Towards Better Cephalometric Landmark Detection with Diffusion Data Generation | Paper Citation Record

Observation b9b4d6eb-c065-472c-89ca-f3f3a96421d9 · outbound

This paper cites Application of artificial intelligence (ai) in a cephalo- metric analysis: A narrative review,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Application of artificial intelligence (ai) in a cephalo- metric analysis: A narrative review,

Reference 1

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Observation b927434f-b3f2-4dc3-a928-d5dc730ac56e · outbound

This paper cites Missing mri pulse sequence synthesis using multi-modal generative adversarial network,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Missing mri pulse sequence synthesis using multi-modal generative adversarial network,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.650235Z

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Observation 5caa608c-e655-4ace-be06-c11cbf370b64 · outbound

This paper cites Artificial intelligence and machine learning for automated cephalometric landmark identification: A meta-analysis previewed by a systematic review,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Artificial intelligence and machine learning for automated cephalometric landmark identification: A meta-analysis previewed by a systematic review,

Reference 3

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Observation 79ada0bc-9f89-4db8-ac1b-eea26584f57f · outbound

This paper cites Hi-net: hybrid-fusion network for multi-modal mr image synthesis,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Hi-net: hybrid-fusion network for multi-modal mr image synthesis,

Reference 4

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Observation 2364394c-d4f0-4f1f-98f2-8cc3f9ff22bc · outbound

This paper cites Cross-modality image synthesis via weakly coupled and geometry co-regularized joint dictionary learn- ing,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cross-modality image synthesis via weakly coupled and geometry co-regularized joint dictionary learn- ing,

Reference 5

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Observation 3a6c7907-891a-42ab-aee5-33080a9fba01 · outbound

This paper cites Evaluation and comparison of anatomical landmark detection methods for cephalometric x-ray images: a grand challenge,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Evaluation and comparison of anatomical landmark detection methods for cephalometric x-ray images: a grand challenge,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.596055Z

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Observation 2a7a272e-6432-4243-91a4-b551149dfc75 · outbound

This paper cites Chest x-ray generation and data augmentation for cardiovascular abnormality classification,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Chest x-ray generation and data augmentation for cardiovascular abnormality classification,

Reference 7

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Observation 566484c5-f2f2-44b2-a76e-977f70fa79e0 · outbound

This paper cites A benchmark for comparison of dental radiography analysis algorithms,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation A benchmark for comparison of dental radiography analysis algorithms,

Reference 8

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Observation 0f0785a7-9d4d-48f9-b441-858f51a65869 · outbound

This paper cites Genera- tion of synthetic chest x-ray images and detection of covid-19: A deep learning based approach,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Genera- tion of synthetic chest x-ray images and detection of covid-19: A deep learning based approach,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.554315Z

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Observation 91fdcb6c-304a-4517-9780-967fd540cb84 · outbound

This paper cites Diverse data generation for retinal layer segmentation with potential structure modelling,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Diverse data generation for retinal layer segmentation with potential structure modelling,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.539652Z

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Observation c6f0bb0c-ced3-4e2b-bbca-efd154130a35 · outbound

This paper cites Generative adversarial nets,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Generative adversarial nets,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.525852Z

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Observation d24318e8-1061-4f0c-b742-e91520b4716e · outbound

This paper cites Generation of 3d brain mri using auto-encoding generative adversarial networks,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Generation of 3d brain mri using auto-encoding generative adversarial networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.512707Z

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Observation fecc8fe2-29ab-4cda-abe7-c876ef31c565 · outbound

This paper cites GANs for Medical Image Synthesis: An Empirical Study.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation GANs for Medical Image Synthesis: An Empirical Study

Reference 13

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Observation 2d774f84-9bb2-41ac-bfb1-f901c75ad4c4 · outbound

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

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation High- resolution image synthesis with latent diffusion models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.499862Z

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Observation 96b299b6-8733-4626-b4ea-44c0bcc5e17a · outbound

This paper cites Deep high-resolution representation learning for visual recognition,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Deep high-resolution representation learning for visual recognition,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.486536Z

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Observation 38164dbd-1d91-42bf-a82c-7901ec0fc3a4 · outbound

This paper cites Cascaded latent diffusion models for high-resolution chest x-ray synthesis,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cascaded latent diffusion models for high-resolution chest x-ray synthesis,

Reference 16

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Observation 67f4c215-a408-448f-9665-02ad733c5bac · outbound

This paper cites Cxr-irgen: An integrated vision and language model for the generation of clinically accurate chest x-ray image-report pairs,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cxr-irgen: An integrated vision and language model for the generation of clinically accurate chest x-ray image-report pairs,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.460411Z

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Observation 20e78dac-cc9e-4fc5-9a80-4f682a4f1c38 · outbound

This paper cites PIE: Simulating Disease Progression via Progressive Image Editing.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation PIE: Simulating Disease Progression via Progressive Image Editing

Reference 18

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Observation 99f9e1aa-992c-4450-bdf1-2911dbae8b34 · outbound

This paper cites Medm2g: Unifying medical multi-modal generation via cross-guided diffusion with visual invariant,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Medm2g: Unifying medical multi-modal generation via cross-guided diffusion with visual invariant,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.446838Z

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Observation 2ac0e120-48ce-4345-b362-f914113d932e · outbound

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

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Adding conditional control to text- to-image diffusion models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.433349Z

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Observation 04a84896-7c7a-47ab-a387-746878a41590 · outbound

This paper cites Lc-sd: Realistic endoscopic image generation with limited training data,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Lc-sd: Realistic endoscopic image generation with limited training data,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.419620Z

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Observation 9ddced0d-4970-4a8e-854b-7a20711797e5 · outbound

This paper cites Generative AI for Medical Imaging: extending the MONAI Framework.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Generative AI for Medical Imaging: extending the MONAI Framework

Reference 22

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Observation 3bc7af1a-907f-4e3b-b7c7-bc9e1a33b011 · outbound

This paper cites Knowledge- based landmarking of cephalograms,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Knowledge- based landmarking of cephalograms,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.406314Z

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Observation f03ba025-f523-4667-8c84-b65170283dd9 · outbound

This paper cites An image processing system for cephalometric analysis and measurements,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation An image processing system for cephalometric analysis and measurements,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.392991Z

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Observation 3b2bb884-e9db-4fa0-879c-124be606de8d · outbound

This paper cites Cephalometric landmarks localization based on histograms of oriented gradients,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cephalometric landmarks localization based on histograms of oriented gradients,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.379117Z

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Observation 775cc9e5-c760-4368-aceb-020cf475802c · outbound

This paper cites Automatic cephalo- metric x-ray landmark detection by applying game theory and random forests,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Automatic cephalo- metric x-ray landmark detection by applying game theory and random forests,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.363949Z

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Observation a00442df-e3bb-4dbd-aaf9-0904a1f18306 · outbound

This paper cites Fully automatic cephalometric evaluation using random forest regression-voting,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Fully automatic cephalometric evaluation using random forest regression-voting,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.349092Z

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Observation f4b85ca3-6371-4663-b13e-a30a1258c771 · outbound

This paper cites Fully automatic system for accurate localisation and analysis of cephalometric landmarks in lateral cephalograms,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Fully automatic system for accurate localisation and analysis of cephalometric landmarks in lateral cephalograms,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.334541Z

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Observation 16420a90-5878-426c-99f5-48ff7c460782 · outbound

This paper cites Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:54:10.881998Z

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Observation 03cb8ef3-8d60-4541-9029-88e159cb7f03 · outbound

This paper cites Deep Learning based Cephalometric Landmark Identification using Landmark-dependent Multi-scale Patches.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Deep Learning based Cephalometric Landmark Identification using Landmark-dependent Multi-scale Patches

Reference 30

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Observation df12c1c8-eb23-499a-9b55-94767537d207 · outbound

This paper cites Cephalometric landmark detection by attentive feature pyramid fusion and regression- voting,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cephalometric landmark detection by attentive feature pyramid fusion and regression- voting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.319197Z

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Observation 5835347e-8f6e-4a55-b0d0-afea0b1567cc · outbound

This paper cites Cephalformer: incorporating global structure constraint into visual features for general cephalometric landmark detection,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cephalformer: incorporating global structure constraint into visual features for general cephalometric landmark detection,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.302423Z

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Observation ed198f43-c6a9-45cc-8462-1f9eb7246d74 · outbound

This paper cites Uod: Universal one-shot detection of anatomical landmarks,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Uod: Universal one-shot detection of anatomical landmarks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.287641Z

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Observation 8d9bedd4-2364-4e98-8d19-ffbc8d12817e · outbound

This paper cites The frankfort-mandibular plane angle in orthodontic diagnosis, classification, treatment planning, and prognosis,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation The frankfort-mandibular plane angle in orthodontic diagnosis, classification, treatment planning, and prognosis,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.273911Z

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Observation 38af66c6-7ef4-4ad2-b1be-b7d3442e74e6 · outbound

This paper cites Cephalometrics for you and me,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cephalometrics for you and me,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.260501Z

Source-reported events for the cited work

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Observation 6fbf3ca3-c669-4548-a0c2-71c249529360 · outbound

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

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Learning transferable visual models from natural language supervision,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.247304Z

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Observation cb243c13-4763-4ff8-b2c0-4bbdda71be5c · outbound

This paper cites Deep residual learning for image recognition,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Deep residual learning for image recognition,

Reference 37

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Observation 1b5012dd-5b43-42a6-91ef-9fa5f9763686 · outbound

This paper cites Simple baselines for human pose estimation and tracking,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Simple baselines for human pose estimation and tracking,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.224054Z

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Observation 4090eda3-f089-47ee-9e1d-191b59b616be · outbound

This paper cites Cascaded convolutional networks for automatic cephalometric landmark detection,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cascaded convolutional networks for automatic cephalometric landmark detection,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.209392Z

Source-reported events for the cited work

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Observation 0397c984-b26c-41e7-bf58-52b8858a55f7 · outbound

This paper cites Cephalometric landmark detection in lateral x-ray images 2023,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Cephalometric landmark detection in lateral x-ray images 2023,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.195850Z

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Observation 5610c612-0ef1-4d19-bc53-b8f46dba66c6 · outbound

This paper cites Diffusers: State-of-the-art diffusion models,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Diffusers: State-of-the-art diffusion models,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.183359Z

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Observation 6d3dff7d-09b3-44db-9ab2-f3b3518b18ad · outbound

This paper cites Which images to label for few-shot medical landmark detection?.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Which images to label for few-shot medical landmark detection?

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.170228Z

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Observation 1b837098-36d2-492a-8a7e-52544abd6d9c · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 43

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Observation a141ed7a-29bd-4eb9-ab0c-d2cfded9d37c · outbound

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

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T22:54:10.945246Z

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Observation 8a5e4cc4-c00b-4ee0-884b-5ad4208125d9 · outbound

This paper cites Floating norms for individualising the anb angle and the wits appraisal in orthodontic cephalometric analysis based on guiding variables,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Floating norms for individualising the anb angle and the wits appraisal in orthodontic cephalometric analysis based on guiding variables,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.156102Z

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Observation 49cea5d0-c83a-4809-ba9e-0459ad4b3786 · outbound

This paper cites Synthetic data in machine learning for medicine and healthcare,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Synthetic data in machine learning for medicine and healthcare,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:54:10.953569Z

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Observation 9d5977bb-9425-470f-adb0-f7895c53c09b · outbound

This paper cites Data augmentation for medical imaging: A systematic literature review,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Data augmentation for medical imaging: A systematic literature review,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:54:10.957643Z

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Observation 7fa4acfd-bf54-4308-a0a8-3453c2bff271 · outbound

This paper cites Synthetic data generation methods in healthcare: A review on open-source tools and methods,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Synthetic data generation methods in healthcare: A review on open-source tools and methods,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.125602Z

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Observation 23bc5ff0-b8fd-401d-8ea9-a578325c0cc7 · outbound

This paper cites Addressing medical imaging limitations with synthetic data generation,.

Towards Better Cephalometric Landmark Detection with Diffusion Data Generation Addressing medical imaging limitations with synthetic data generation,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:54:11.112071Z

Source-reported events for the cited work

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