Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T14:57:38.357605Z
Paper Citation Record · LEDGER
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network
As of 22 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2508.20734.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
62 of 62 outbound references displayed
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- verified fuzzy57
- unresolved3
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3988eda1-2eef-4e43-88eb-4b8387d17629 · outbound
This paper cites Global atlas on cardiovascular disease prevention and control.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Global atlas on cardiovascular disease prevention and control
Reference 1
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 86a650a1-1c85-4c41-9d19-37020ea7bc84 · outbound
This paper cites European cardiovascular disease statistics 2017.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network European cardiovascular disease statistics 2017
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ab68d9ff-70b9-4201-b150-fc90a6debf1d · outbound
This paper cites an unresolved cited work.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Unresolved cited work
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation aa6577c8-b939-4c3c-a6f6-32774ad9617f · outbound
This paper cites BHF CVD Statistics UK Factsheet, 2022.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network BHF CVD Statistics UK Factsheet, 2022
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.260279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e958fb11-d18b-4b58-ac9a-c1fdfaf815a4 · outbound
This paper cites Challenges and opportu- nities for cardiovascular disease prevention.The American journal of medicine, 124(2):95–102, 2011.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Challenges and opportu- nities for cardiovascular disease prevention.The American journal of medicine, 124(2):95–102, 2011
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.246754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 176453b2-4784-48ff-9f84-54185c573862 · outbound
This paper cites State of the science: the relevance of symptoms in cardiovascular disease and research: a scientific statement from the american heart association.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network State of the science: the relevance of symptoms in cardiovascular disease and research: a scientific statement from the american heart association
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.232558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ea713a9d-34e2-414f-9898-4110c0ebcbc4 · outbound
This paper cites Het- erogeneity of cardiovascular disease risk factors among asian immigrants: insights from the 2010 to 2018 national health interview survey.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Het- erogeneity of cardiovascular disease risk factors among asian immigrants: insights from the 2010 to 2018 national health interview survey
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.217699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b1a0129a-0453-4ff4-8d8c-54e6d7afa5f2 · outbound
This paper cites Cvd screening in low-risk, asymptomatic adults: clinical trials needed.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Cvd screening in low-risk, asymptomatic adults: clinical trials needed
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.203185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fce4c8a5-8922-4bfc-996a-d68ade475c5d · outbound
This paper cites The association of abnormal ventricular wall motion and increased dispersion of repolarization in humans is independent of the presence of myocardial infarction.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network The association of abnormal ventricular wall motion and increased dispersion of repolarization in humans is independent of the presence of myocardial infarction
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.188730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1dc33140-8904-4f93-a097-c9760f99cc1d · outbound
This paper cites Usefulness of the severity and extent of wall motion abnormalities as prognostic markers of an adverse outcome after a first myocardial infarction treated with thrombolytic therapy.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Usefulness of the severity and extent of wall motion abnormalities as prognostic markers of an adverse outcome after a first myocardial infarction treated with thrombolytic therapy
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.174893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 17c88919-7c27-4d48-aa0e-c9c90f74935b · outbound
This paper cites Prevalence and prognostic significance of wall-motion abnormalities in adults without clinically recognized cardiovascular disease: the strong heart study.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Prevalence and prognostic significance of wall-motion abnormalities in adults without clinically recognized cardiovascular disease: the strong heart study
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.160881Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation bda975fb-368c-45d8-9a8e-5e3a20ba5b7f · outbound
This paper cites Recent advances in cardiovascular magnetic resonance: techniques and applications.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Recent advances in cardiovascular magnetic resonance: techniques and applications
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.146412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b3dd247d-4ae5-4978-a0b7-d7a271cc791a · outbound
This paper cites Deep-learning cardiac motion analysis for human survival prediction.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Deep-learning cardiac motion analysis for human survival prediction
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.131685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a376be13-3be9-41ff-8e31-09cb57743c24 · outbound
This paper cites Cardiac mr: from theory to practice.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Cardiac mr: from theory to practice
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.117633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ed1f82b0-c3ed-4db8-9283-44565e2ebdeb · outbound
This paper cites Intra-observer and interobserver variability of biven- tricular function, volumes and mass in patients with congenital heart disease measured by cmr imaging.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Intra-observer and interobserver variability of biven- tricular function, volumes and mass in patients with congenital heart disease measured by cmr imaging
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.103446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f5b3de49-f8fc-44d9-a65e-f4ae3e2f0757 · outbound
This paper cites Cardiac motion tracking using cine harmonic phase (harp) magnetic resonance imaging.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Cardiac motion tracking using cine harmonic phase (harp) magnetic resonance imaging
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.088836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 30cb137b-e624-4836-8011-203a173eb6fc · outbound
This paper cites Automated 3d motion tracking using gabor filter bank, robust point matching, and deformable models.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Automated 3d motion tracking using gabor filter bank, robust point matching, and deformable models
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.074600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 384436c5-038d-4d53-b1b1-8c8d96925a78 · outbound
This paper cites Incompressible deformation estimation algorithm (idea) from tagged mr images.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Incompressible deformation estimation algorithm (idea) from tagged mr images
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.060796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 82026057-6ff1-4e76-b786-c799eb2ebb45 · outbound
This paper cites Fast lv motion estimation using subspace approximation techniques.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Fast lv motion estimation using subspace approximation techniques
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.047371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6cef39a8-c11e-4d17-aea4-d0c0240fbb8c · outbound
This paper cites Estimation of 3d left ventricular deformation from echocardiography.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Estimation of 3d left ventricular deformation from echocardiography
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.033554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 645d223a-48db-46dd-acbc-93d8820c2308 · outbound
This paper cites Nonrigid registration using free-form deformations: application to breast mr images.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Nonrigid registration using free-form deformations: application to breast mr images
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.016470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 16956375-31c9-470c-8b56-2ee9abed4334 · outbound
This paper cites Tem- poral diffeomorphic free-form deformation: Application to motion and strain estimation from 3d echocardiography.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Tem- poral diffeomorphic free-form deformation: Application to motion and strain estimation from 3d echocardiography
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:39.003402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e8658aa3-a08e-4c99-a35c-60046511e801 · outbound
This paper cites Consistent estimation of cardiac motions by 4d image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Consistent estimation of cardiac motions by 4d image registration
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.989814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c8f1d6da-c590-4a09-a986-33e78b081ba8 · outbound
This paper cites Analysis of 3-d myocardial motion in tagged mr images using nonrigid image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Analysis of 3-d myocardial motion in tagged mr images using nonrigid image registration
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.976343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 51e39387-ad38-4790-adf0-8911460af39e · outbound
This paper cites A compre- hensive cardiac motion estimation framework using both untagged and 3-d tagged mr images based on nonrigid registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A compre- hensive cardiac motion estimation framework using both untagged and 3-d tagged mr images based on nonrigid registration
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.962558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4e8f1978-8010-403f-a371-f99840eafd61 · outbound
This paper cites Benchmarking framework for myocardial tracking and deformation algorithms: An open access database.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Benchmarking framework for myocardial tracking and deformation algorithms: An open access database
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.949090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation da579aa6-0911-4822-92eb-8914cfa7f5a9 · outbound
This paper cites Image matching as a diffusion process: an analogy with maxwell’s demons.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Image matching as a diffusion process: an analogy with maxwell’s demons
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.935466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ccfca5f5-1a4a-4c10-9c82-4ea43d9fef7e · outbound
This paper cites Non-parametric diffeomorphic image registration with the demons algorithm.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Non-parametric diffeomorphic image registration with the demons algorithm
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.921579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a29487d1-5e73-4568-afce-ce7693e49e2e · outbound
This paper cites An incompressible log-domain demons algorithm for tracking heart tissue.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network An incompressible log-domain demons algorithm for tracking heart tissue
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.907346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 01c1d4ff-b8d6-40e5-9970-55c28b7b6043 · outbound
This paper cites Deep learning in medical image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Deep learning in medical image registration
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.892929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2be473aa-cd0f-44ec-8e71-d669d1730dfc · outbound
This paper cites Real- time deep pose estimation with geodesic loss for image-to-template rigid registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Real- time deep pose estimation with geodesic loss for image-to-template rigid registration
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.878585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ceaf0ae8-9e3b-400b-bfe5-45c4ea25febe · outbound
This paper cites Pulmonary ct registration through supervised learn- ing with convolutional neural networks.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Pulmonary ct registration through supervised learn- ing with convolutional neural networks
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.864315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 37a016ff-1d3c-4395-8447-d15567f0fd4d · outbound
This paper cites Deformable image registration using convolutional neural networks.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Deformable image registration using convolutional neural networks
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.850390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 58f9a530-fde8-4579-bc9f-e7948f2cb813 · outbound
This paper cites Gdl-fire: Deep learning-based fast 4d ct image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Gdl-fire: Deep learning-based fast 4d ct image registration
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.836788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 309f0a0f-baff-440b-b9ba-28f0df377671 · outbound
This paper cites Birnet: Brain image reg- istration using dual-supervised fully convolutional networks.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Birnet: Brain image reg- istration using dual-supervised fully convolutional networks
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.822949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4f1f4836-e8c1-4037-9924-d4f7479b5c9d · outbound
This paper cites Training cnns for image registration from few samples with model-based data augmentation.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Training cnns for image registration from few samples with model-based data augmentation
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.808351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation cced3a89-3055-47f0-87d8-bf535540977c · outbound
This paper cites 3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network 3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T14:57:38.461665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4261c9ce-f113-4811-98ea-8d35ee3bc546 · outbound
This paper cites Flownet: Learning optical flow with convolutional networks.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Flownet: Learning optical flow with convolutional networks
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.794680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2addda66-6eaa-4176-b834-d780cac76b9b · outbound
This paper cites Voxel- morph: a learning framework for deformable medical image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Voxel- morph: a learning framework for deformable medical image registration
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.780913Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5dc82fd5-471b-464d-b3e0-f25f1fbc4649 · outbound
This paper cites Symmetric diffeo- morphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Symmetric diffeo- morphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.766369Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation bf9e7e5a-9198-4f25-bf36-3f89d4348477 · outbound
This paper cites A reproducible evaluation of ants similarity metric performance in brain image registra- tion.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A reproducible evaluation of ants similarity metric performance in brain image registra- tion
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.751714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 86f19f9b-6de2-4615-8341-a75d170373d6 · outbound
This paper cites Global image registration using a symmetric block-matching approach.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Global image registration using a symmetric block-matching approach
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.736732Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 62526117-3c05-45b0-900b-00ed0e7e0692 · outbound
This paper cites Fast free-form deformation using graphics processing units.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Fast free-form deformation using graphics processing units
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.722379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b3cf94d5-a6b9-4b82-adb9-ce8658a6d8c3 · outbound
This paper cites Cnn-based cardiac motion extraction to generate deformable geometric left ventricle myocardial models from cine mri.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Cnn-based cardiac motion extraction to generate deformable geometric left ventricle myocardial models from cine mri
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.708642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e002f60d-351a-4ff0-bf8f-47e7cf5f8319 · outbound
This paper cites A deep learning framework for unsupervised affine and deformable image registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A deep learning framework for unsupervised affine and deformable image registration
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.694308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 42838c43-39d8-42f5-ba6a-b0ea7818e23b · outbound
This paper cites Mulvimotion: Shape-aware 3d myocardial motion tracking from multi- view cardiac mri.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Mulvimotion: Shape-aware 3d myocardial motion tracking from multi- view cardiac mri
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.679976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 74eaa454-3b96-41f4-839a-7245676796f7 · outbound
This paper cites Deepmesh: Mesh-based cardiac motion tracking using deep learning.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Deepmesh: Mesh-based cardiac motion tracking using deep learning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.665600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d07fae34-e85f-4315-bb65-004fd34a7298 · outbound
This paper cites Learn- ing a probabilistic model for diffeomorphic registration.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Learn- ing a probabilistic model for diffeomorphic registration
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.650762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 2e55192b-4a88-4e30-ada4-8bb78840b944 · outbound
This paper cites Dragnet: Learning-based de- formable registration for realistic cardiac mr sequence generation from a single frame.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Dragnet: Learning-based de- formable registration for realistic cardiac mr sequence generation from a single frame
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.637513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e1a7d035-382b-4cd6-b153-4e2daf717fb6 · outbound
This paper cites Joint learning of motion estimation and segmentation for cardiac mr image sequences.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Joint learning of motion estimation and segmentation for cardiac mr image sequences
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.623705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e7f08dcf-c9c0-4fb4-8e49-9e0c3fd0ae31 · outbound
This paper cites Segmorph: Concurrent motion estimation and segmentation for cardiac mri sequences.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Segmorph: Concurrent motion estimation and segmentation for cardiac mri sequences
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.609649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ba49d3ba-d43c-40bf-b86e-4084a9e6d459 · outbound
This paper cites Auto-Encoding Variational Bayes.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Auto-Encoding Variational Bayes
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:57:38.310434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 26a4df23-f8e1-44f4-96c0-686bc32a545d · outbound
This paper cites Back to basics: Unsuper- vised learning of optical flow via brightness constancy and motion smoothness.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Back to basics: Unsuper- vised learning of optical flow via brightness constancy and motion smoothness
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.593100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d2b5a28f-fe1a-4b69-9fd9-207868b01526 · outbound
This paper cites Automated car- diovascular magnetic resonance image analysis with fully convolutional networks.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Automated car- diovascular magnetic resonance image analysis with fully convolutional networks
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.576981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 642c2b09-18bb-4bbe-bd71-1b7c081f8056 · outbound
This paper cites Mesh-based 3d motion tracking in cardiac mri using deep learning.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Mesh-based 3d motion tracking in cardiac mri using deep learning
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.561356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 1a20cd4d-3d3c-4829-86e3-1f71ece97709 · outbound
This paper cites MONAI: An open-source framework for deep learning in healthcare.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network MONAI: An open-source framework for deep learning in healthcare
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:57:38.329533Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea95d931-ea5b-4235-a871-3e70689e50a6 · outbound
This paper cites Lcc-demons: a robust and accurate symmetric diffeo- morphic registration algorithm.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Lcc-demons: a robust and accurate symmetric diffeo- morphic registration algorithm
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.545101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7a70446c-42e9-4801-bcc7-0a39f63abea7 · outbound
This paper cites A fast diffeomorphic image registration algorithm.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A fast diffeomorphic image registration algorithm
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.527491Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 69231e46-bbd4-4a60-a1c0-c08dcdcb3133 · outbound
This paper cites Joint segmentation and discontinuity-preserving deformable registration: Application to cardiac cine-MR images.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Joint segmentation and discontinuity-preserving deformable registration: Application to cardiac cine-MR images
Reference 59
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T14:57:38.404503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 067a1887-4e79-41c1-a82f-2c53725dc6ac · outbound
This paper cites A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.511382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7bd4e831-faa7-45b5-a75d-bcedb053e8c3 · outbound
This paper cites Multiresolution extended free-form deformations (xffd) for non-rigid registration with discontinuous transforms.Medical image analysis , 36:113–122, 2017.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network Multiresolution extended free-form deformations (xffd) for non-rigid registration with discontinuous transforms.Medical image analysis , 36:113–122, 2017
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.494003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 556873cb-58f5-4c9d-9c5f-9a072fbd0507 · outbound
This paper cites A bi-ventricular cardiac atlas built from 1000+ high resolution mr images of healthy subjects and an analysis of shape and motion.
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network A bi-ventricular cardiac atlas built from 1000+ high resolution mr images of healthy subjects and an analysis of shape and motion
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:57:38.477753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.