Paper Citation Record · LEDGER

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection

As of 15 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 3 inbound Pith citation observations for arXiv:2412.06499.

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

pith.paper-citation-record.v1
2412.06499 v2

Coverage vector

measured 48 of 48 reference resolution

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measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:17:31.175070Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

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arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6fa93e5b-87d3-4020-9a2c-e14f1e079b4b · outbound

This paper cites Handbook of medical image computing and computer assisted intervention.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Handbook of medical image computing and computer assisted intervention

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.293684Z

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Observation d2f006cf-a4b7-4d28-8a3f-8e2c559dcb53 · outbound

This paper cites Percutaneous vertebral surgery.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Percutaneous vertebral surgery

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.283909Z

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Observation 2b797966-9cf2-4a42-8210-9c234b6a7cdc · outbound

This paper cites Evaluation and comparison of anatomical landmark detection methods for cephalo- metric x-ray images: a grand challenge.IEEE trans- actions on medical imaging, 34(9):1890–1900, 2015.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Evaluation and comparison of anatomical landmark detection methods for cephalo- metric x-ray images: a grand challenge.IEEE trans- actions on medical imaging, 34(9):1890–1900, 2015

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.274662Z

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Observation 9b277fc7-2870-4846-96e7-f8b40ece5128 · outbound

This paper cites Robust anatomical land- mark detection for mr brain image registration.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Robust anatomical land- mark detection for mr brain image registration

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.264840Z

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Observation eb1388cb-2f58-43f3-a241-3c0d7dce46cb · outbound

This paper cites IEEE transactions on medical imaging, 36(1):332– 342, 2016.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection IEEE transactions on medical imaging, 36(1):332– 342, 2016

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.253471Z

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Observation d4818707-0a3e-4b8b-a92a-33efd7180549 · outbound

This paper cites DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models

Reference 6

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Observation c4e5d54f-fa1a-4f73-893a-349a37b6d9a1 · outbound

This paper cites Parametric modelling and segmentation of vertebralbodiesin3dctandmrspineimages.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Parametric modelling and segmentation of vertebralbodiesin3dctandmrspineimages

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.243334Z

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Observation 756534ea-55cf-479e-a675-d299ca7df1d3 · outbound

This paper cites Robust and accurate shape model matchingusingrandomforestregression-voting.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Robust and accurate shape model matchingusingrandomforestregression-voting

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.213545Z

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Observation a4aaa697-f840-4d28-9f11-fc161227ec2a · outbound

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

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection U-net: Convolutional networks for biomedical image segmentation

Reference 11

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Observation 5fb3b7cd-f2c3-4532-a558-aedbba5e6aa3 · outbound

This paper cites Regressing heatmaps for multiple land- mark localization using cnns.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Regressing heatmaps for multiple land- mark localization using cnns

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.196437Z

Source-reported events for the cited work

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Observation e120d481-5436-496c-8e04-44d69bc1cd02 · outbound

This paper cites Cephalometric landmark detection in dental x-ray im- ages using convolutional neural networks.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Cephalometric landmark detection in dental x-ray im- ages using convolutional neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.186571Z

Source-reported events for the cited work

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Observation 98c3c5d5-0b70-4d6d-81cd-119875c6c3d3 · outbound

This paper cites Attaininghuman-levelper- formance with atlas location autocontext for anatomi- callandmarkdetectionin3dctdata.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Attaininghuman-levelper- formance with atlas location autocontext for anatomi- callandmarkdetectionin3dctdata

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.176082Z

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Observation 20669971-0344-4eeb-9556-ea0702c61012 · outbound

This paper cites Integrating spatial configuration into heatmap regression based cnns for landmark localiza- tion.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Integrating spatial configuration into heatmap regression based cnns for landmark localiza- tion

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.165521Z

Source-reported events for the cited work

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Observation 70e5d0f6-1b6b-4df3-827e-fae09c4173a7 · outbound

This paper cites Feature aggregation and refinement network for 2d anatomical landmark detection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Feature aggregation and refinement network for 2d anatomical landmark detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.154830Z

Source-reported events for the cited work

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Observation 8bb62433-6b93-4f2d-8bd3-08cf6a819ba2 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 17

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Observation c057d7f4-0598-47aa-b068-7d3dc97a2fb8 · outbound

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

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 18

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Observation e085eeee-7700-408a-835b-6b912ee4a5f3 · outbound

This paper cites Utnet: a hybrid transformer architecture for medical image segmentation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Utnet: a hybrid transformer architecture for medical image segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.136566Z

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Observation c7d40075-7854-4b87-a945-c863ec32b656 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 20

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Observation df88aeb4-173d-4fd8-b98f-2ef8c83b0351 · outbound

This paper cites nnFormer: Interleaved Transformer for Volumetric Segmentation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection nnFormer: Interleaved Transformer for Volumetric Segmentation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T19:40:02.686781Z

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Observation ec337903-7555-4e38-a7be-e9aee2f1550b · outbound

This paper cites Spinehrformer: A transformer-based deep learning model for automatic spine deformity assessment with prospective validation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Spinehrformer: A transformer-based deep learning model for automatic spine deformity assessment with prospective validation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.126247Z

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Observation 26d059ab-7a34-4894-be31-8c60bcab938c · outbound

This paper cites DATR: Domain-adaptive transformer for multi-domain landmark detection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection DATR: Domain-adaptive transformer for multi-domain landmark detection

Reference 23

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Observation 48e564f4-b989-48e4-b57e-c0722d536caa · outbound

This paper cites In International Conference on Medical X.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection In International Conference on Medical X

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.116944Z

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Observation f5ebcdaa-8872-44db-b91b-67273b7f303b · outbound

This paper cites Cephalformer: incorporat- ing global structure constraint into visual features for general cephalometric landmark detection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Cephalformer: incorporat- ing global structure constraint into visual features for general cephalometric landmark detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.107905Z

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Observation 4f7410ea-4b15-4a98-a1f0-4ae5288b4b2b · outbound

This paper cites Medical transformer: Gatedaxial-attentionformedicalimagesegmentation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Medical transformer: Gatedaxial-attentionformedicalimagesegmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.098042Z

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Observation 9a58a104-ec8d-47b7-8879-6489948f52bf · outbound

This paper cites A multi-stage en- semble network system to diagnose adolescent idio- pathic scoliosis.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection A multi-stage en- semble network system to diagnose adolescent idio- pathic scoliosis

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.088349Z

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Observation d52fca71-6bcb-43ab-8d9f-12dd253416f0 · outbound

This paper cites Object recognition from local scale- invariant features.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Object recognition from local scale- invariant features

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.233338Z

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Observation f669e723-8e5e-4da6-88cd-a12950df13d4 · outbound

This paper cites Automatic computerized radiographic identification of cephalo- metric landmarks.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Automatic computerized radiographic identification of cephalo- metric landmarks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.078282Z

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Observation 8238161c-7561-495e-9047-56075fbbf223 · outbound

This paper cites Automatic localization of cephalometric landmarks.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Automatic localization of cephalometric landmarks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.067003Z

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Observation 84eb9cc4-782e-44b9-a88a-33c8a47fc038 · outbound

This paper cites Search strategies for multiple land- mark detection by submodular maximization.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Search strategies for multiple land- mark detection by submodular maximization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.223787Z

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Observation c8c462b7-de21-4ec5-8a90-bdded51f4940 · outbound

This paper cites An image processingsystemforlocatingcraniofaciallandmarks.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection An image processingsystemforlocatingcraniofaciallandmarks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.056768Z

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Observation e08d92ff-35a0-4e57-bf2b-3892cd26a6df · outbound

This paper cites Automatic localization of craniofacial land- marks for assisted cephalometry.Pattern Recognition, 37(3):609–621, 2004.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Automatic localization of craniofacial land- marks for assisted cephalometry.Pattern Recognition, 37(3):609–621, 2004

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.045880Z

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Observation 6a5a6e94-51f7-4926-9793-053e4beacbf3 · outbound

This paper cites Automated cephalo- metric landmark identification using shape and local appearancemodels.In 201020thInternationalConfer- enceonPatternRecognition ,pages2464–2467.IEEE, 2010.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Automated cephalo- metric landmark identification using shape and local appearancemodels.In 201020thInternationalConfer- enceonPatternRecognition ,pages2464–2467.IEEE, 2010

Reference 34

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This paper cites an unresolved cited work.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Unresolved cited work

Reference 35

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Observation 4cc779f3-e941-4b87-bd32-5e4d1dc6c6bf · outbound

This paper cites You only learn once: Universal anatomical landmark detection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection You only learn once: Universal anatomical landmark detection

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.016510Z

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Observation c11198a4-8d48-483a-8262-96067879417a · outbound

This paper cites Anatomical landmark detection in chest x-ray images using transformer-based networks.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Anatomical landmark detection in chest x-ray images using transformer-based networks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:03.007259Z

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Observation 20ef052e-1e8a-4de0-8005-c71db3977cc9 · outbound

This paper cites Swin- unet: Unet-like pure transformer for medical image segmentation.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Swin- unet: Unet-like pure transformer for medical image segmentation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.997599Z

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Observation a606f8ef-bf9b-4309-abeb-39ac13a2365a · outbound

This paper cites Swin transformer com- bined with convolutional encoder for cephalometric landmarksdetection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Swin transformer com- bined with convolutional encoder for cephalometric landmarksdetection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.987608Z

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Observation 1150226d-2c15-4657-9f7f-48533732f77e · outbound

This paper cites Swin transformer: Hierarchical vision transformer us- ingshiftedwindows.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Swin transformer: Hierarchical vision transformer us- ingshiftedwindows

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.977112Z

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Observation 35ec7ab9-d139-4530-813c-c4ce692362b1 · outbound

This paper cites Biformer: Vision transformer with bi-level routing attention.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Biformer: Vision transformer with bi-level routing attention

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.966885Z

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Observation 78cf467b-3594-41f4-ad1d-fa350b67b314 · outbound

This paper cites Visiontransformerwithdeformableatten- tion.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Visiontransformerwithdeformableatten- tion

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.956503Z

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Observation adb865b4-1285-4c14-b165-59b7cc58985b · outbound

This paper cites Cbam: Convolutional block attention module.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Cbam: Convolutional block attention module

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.946233Z

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Observation e3cb934c-28d3-453b-b383-a8959cd39076 · outbound

This paper cites A benchmark for comparison of dentalradiographyanalysisalgorithms.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection A benchmark for comparison of dentalradiographyanalysisalgorithms

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.935067Z

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Observation 567df278-9ecf-49af-8c95-af965bd1e606 · outbound

This paper cites CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023

Reference 45

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Observation 79b4c73f-cad8-4808-a879-b1b9170c84f5 · outbound

This paper cites In International Conference on Medical Image ComputingandComputer-AssistedIntervention ,pages 155–165.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection In International Conference on Medical Image ComputingandComputer-AssistedIntervention ,pages 155–165

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.924738Z

Source-reported events for the cited work

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Observation 09771512-29ec-47b3-967f-f0a48089d7f4 · outbound

This paper cites A scalable physician-level deep learning algorithm de- tects universal trauma on pelvic radiographs.Nature communications, 12(1):1066, 2021.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection A scalable physician-level deep learning algorithm de- tects universal trauma on pelvic radiographs.Nature communications, 12(1):1066, 2021

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.914528Z

Source-reported events for the cited work

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Observation 5079c889-1270-49a1-bc27-5b4b6412fc16 · outbound

This paper cites Pele scores: pelvic x-ray landmark detection with pelvis extraction and enhancement.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Pele scores: pelvic x-ray landmark detection with pelvis extraction and enhancement

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.902956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a4b47ee8-2641-41a3-b0c4-24845e90fffd · outbound

This paper cites Cascade r-cnn: Delvingintohighqualityobjectdetection.

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Cascade r-cnn: Delvingintohighqualityobjectdetection

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:02.891871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 36bd80d0-aae6-4770-9d61-ae5255313a24 · outbound

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

HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:02.823267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation e6436e47-e278-47eb-a64d-e29dadae665e · inbound

U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKV cites this paper.

U-RWKV: Lightweight medical image segmentation with direction-adaptive RWKV HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T17:17:31.175070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f2c4fbf-e453-4276-824c-c39589d4acdd · inbound

SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training cites this paper.

SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T20:51:06.725736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 250f8764-2c73-4670-9cd3-fe2f9d55f603 · inbound

CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection cites this paper.

CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection HYATT-Net is Grand: A Hybrid Attention Network for Performant Anatomical Landmark Detection

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-28T06:51:44.936310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.