A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images | Paper Citation Record

Observation 047e0277-5403-4d29-bc26-512af3860cc2 · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Deep Learning using Rectified Linear Units (ReLU)

Reference 1

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This paper cites University of Salford (United Kingdom), 2017.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images University of Salford (United Kingdom), 2017

Reference 2

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This paper cites Elastic matching of diusion tensor images.Computer Vision and Image Understanding, 77(2):233–250, 2000.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Elastic matching of diusion tensor images.Computer Vision and Image Understanding, 77(2):233–250, 2000

Reference 3

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This paper cites John mccarthy: father of ai.IEEE Intelligent Systems, 17(5):84–85, 2002.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images John mccarthy: father of ai.IEEE Intelligent Systems, 17(5):84–85, 2002

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This paper cites Cardiovascular magnetic resonance in the evaluation of heart failure.Heart, 93(8):985–992, 2007.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Cardiovascular magnetic resonance in the evaluation of heart failure.Heart, 93(8):985–992, 2007

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:09.457017Z

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This paper cites Types of machine learning algorithms.New advances in machine learning, 3:19–48, 2010.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Types of machine learning algorithms.New advances in machine learning, 3:19–48, 2010

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:09.127519Z

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Observation 13ac035f-c7de-41f0-81a5-f98bfa9ae0bf · outbound

This paper cites Voxelmorph: a learning framework for deformable medical image registration.IEEE transactions on medical imaging, 38(8):1788–1800, 2019.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Voxelmorph: a learning framework for deformable medical image registration.IEEE transactions on medical imaging, 38(8):1788–1800, 2019

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This paper cites An empirical study on generalizations of the relu activation function.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images An empirical study on generalizations of the relu activation function

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:08.857121Z

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Observation e28fd54f-4959-4f31-9cca-c4de16ea989f · outbound

This paper cites How do i do it? speckle-tracking echocardiography.Indian heart journal, 65(1):117, 2013.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images How do i do it? speckle-tracking echocardiography.Indian heart journal, 65(1):117, 2013

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:08.728677Z

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This paper cites Some recent applications of reinforcement learning.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Some recent applications of reinforcement learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:08.547784Z

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This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-06T23:13:08.442792Z

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Observation b51cd392-161c-4a5c-bc4f-b200664eb26f · outbound

This paper cites Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:08.301578Z

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Observation 415ff70c-da83-4f9d-8ba8-f0d6c3582727 · outbound

This paper cites From compressed-sensing to articial intelligence-based cardiac mri reconstruction.Frontiers in cardiovascular medicine, 7:17, 2020.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images From compressed-sensing to articial intelligence-based cardiac mri reconstruction.Frontiers in cardiovascular medicine, 7:17, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:08.156405Z

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Observation a05cecaf-444f-4625-b0e1-1f08532b926d · outbound

This paper cites Detection of myocardial scar using t2* in a clinical setting.Journal of Cardiovascular Magnetic Reso- nance, 17:1–2, 2015.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Detection of myocardial scar using t2* in a clinical setting.Journal of Cardiovascular Magnetic Reso- nance, 17:1–2, 2015

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:07.925750Z

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Observation 7d1fec31-41ee-4ce1-b738-8eda66a781e2 · outbound

This paper cites Steady-state free precession in nuclear magnetic resonance.Physical Review, 112(5):1693, 1958.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Steady-state free precession in nuclear magnetic resonance.Physical Review, 112(5):1693, 1958

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:07.690616Z

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This paper cites Applying self- supervised learning to medicine: review of the state of the art and medical implementations.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Applying self- supervised learning to medicine: review of the state of the art and medical implementations

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:07.440881Z

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This paper cites Patch-based discrete registration of clinical brain images.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Patch-based discrete registration of clinical brain images

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Observation f3b29e91-0376-4ea4-9d88-8019bf9ceeb3 · outbound

This paper cites Strain and strain rate imaging by echocardiography-basic concepts and clinical applicability.Current cardiology reviews, 5(2):133–148, 2009.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Strain and strain rate imaging by echocardiography-basic concepts and clinical applicability.Current cardiology reviews, 5(2):133–148, 2009

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:06.962761Z

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Observation dca887a7-efba-4da1-8e7f-888b6ebf2ba1 · outbound

This paper cites The history of echocardiography.Ultrasound in medicine & biology, 30(12):1565–1644, 2004.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images The history of echocardiography.Ultrasound in medicine & biology, 30(12):1565–1644, 2004

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:06.733200Z

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Observation b5533fb1-d183-4d53-99b8-b6c73fdeeec4 · outbound

This paper cites Strain imaging echocardiography: what imag- ing cardiologists should know.Current cardiology reviews, 13(2):118–129, 2017.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Strain imaging echocardiography: what imag- ing cardiologists should know.Current cardiology reviews, 13(2):118–129, 2017

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:06.438395Z

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This paper cites Fda drug safety communication: Fda warns that gadolinium-based contrast agents (gbcas) are retained in the body; requires new class warning.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Fda drug safety communication: Fda warns that gadolinium-based contrast agents (gbcas) are retained in the body; requires new class warning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:06.295732Z

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Observation 5f8cfe2d-7c82-476e-b4cc-d19c35a2a600 · outbound

This paper cites Registration of 3-d intraoperative mr images of the brain using anite-element biomechanical model.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Registration of 3-d intraoperative mr images of the brain using anite-element biomechanical model

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:06.063552Z

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Observation a317c953-9585-4a8a-9783-3f4c1a4e486d · outbound

This paper cites Recent advances in convolutional neural networks.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Recent advances in convolutional neural networks

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Observation ae9eeb19-63ae-41d9-a0ef-5e458d42212a · outbound

This paper cites Digital selection and analogue amplication coexist in a cortex-inspired silicon circuit.nature, 405(6789):947–951, 2000.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Digital selection and analogue amplication coexist in a cortex-inspired silicon circuit.nature, 405(6789):947–951, 2000

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:05.928224Z

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Observation 8e8f4267-24eb-4c4e-ad82-e8846872a2c4 · outbound

This paper cites Machine learning and articial intelligence: denitions, applications, and future directions.Current reviews in musculoskeletal medicine, 13:69–76, 2020.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Machine learning and articial intelligence: denitions, applications, and future directions.Current reviews in musculoskeletal medicine, 13:69–76, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:05.774528Z

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Observation 6b70c450-5d79-41ee-8162-68819633849d · outbound

This paper cites A clinicians guide to tissue doppler imaging.Circulation, 113(10):e396–e398, 2006.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images A clinicians guide to tissue doppler imaging.Circulation, 113(10):e396–e398, 2006

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:05.633455Z

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This paper cites Mechanics of materials: Strainmechanics of slender structures: Boston university, 2013.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Mechanics of materials: Strainmechanics of slender structures: Boston university, 2013

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Observation 0b442d72-e5cc-425e-a6fd-556bfc1a9989 · outbound

This paper cites Unet 3+: A full-scale connected unet for medical image segmentation.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unet 3+: A full-scale connected unet for medical image segmentation

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Observation b40d508b-3630-4096-bd08-a4c3340890da · outbound

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A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Myocardial tagging with mr imaging: overview of normal and pathologicndings.Radiographics, 32(5):1381–1398, 2012

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Observation a0f549fb-12ad-47e1-bd06-8a3fc812e4c0 · outbound

This paper cites Learning a model-driven variational network for deformable image registration.IEEE Transactions on Medical Imaging, 41(1):199–212, 2021.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Learning a model-driven variational network for deformable image registration.IEEE Transactions on Medical Imaging, 41(1):199–212, 2021

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Observation 6e98e9ab-3320-4795-9499-94d4e0f7a4b7 · outbound

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A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Real-time volumetric echocar- diography: the technology and the possibilities.Echocardiography, 17(8):773–779, 2000

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:04.696806Z

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Observation c6b442d9-9462-4148-b652-3cb212ca3f03 · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Observation baada2f8-f49e-4b4d-8c51-baabbf6b01fe · outbound

This paper cites A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 2021.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 2021

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Observation 605b61f8-02bd-452e-9748-4429fd208eea · outbound

This paper cites Rectier nonlinearities improve neural network acoustic models.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Rectier nonlinearities improve neural network acoustic models

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Observation c9d3ffbc-a72b-48bd-aa78-dc87c3c2a0a4 · outbound

This paper cites Articial intelligence and texture analysis in cardiac imaging.Current cardiology reports, 22:1–9, 2020.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Articial intelligence and texture analysis in cardiac imaging.Current cardiology reports, 22:1–9, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:03.820645Z

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Observation 49eaf929-fd42-4c39-9844-20a5b4fbedfa · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Source-reported events for the cited work

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Observation c3374f9e-9798-43d1-b7ac-5ab0940658f1 · outbound

This paper cites Acute myocardial infarction.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Acute myocardial infarction

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Observation c89cf6db-3a53-4e63-b84e-f830f399313c · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-06T23:13:03.310555Z

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Observation 4fbc9cd1-f8a4-4262-ac87-f3ba3c2dcc74 · outbound

This paper cites Introduction to articial intelligence in medicine.Minimally Invasive Therapy & Allied Technologies, 28(2):73–81, 2019.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Introduction to articial intelligence in medicine.Minimally Invasive Therapy & Allied Technologies, 28(2):73–81, 2019

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Observation 9a639ef2-54fe-4027-9a58-f4d05de68280 · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Observation 0400d5bb-6028-4ea9-af8f-ad7f487d5231 · outbound

This paper cites A primer for un- derstanding radiology articles about machine learning and deep learning.Diagnostic and Interventional Imaging, 101(12):765–770, 2020.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images A primer for un- derstanding radiology articles about machine learning and deep learning.Diagnostic and Interventional Imaging, 101(12):765–770, 2020

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:02.639733Z

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Observation e570b63b-9cf4-4540-9c04-108539339623 · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Observation 536cb318-fe3c-40b5-9b43-e5d5029f7f73 · outbound

This paper cites Theory, simulation, and compensation of physiological motion artifacts in functional mri.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Theory, simulation, and compensation of physiological motion artifacts in functional mri

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Source-reported events for the cited work

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Observation dc59a1f2-d438-41d0-b21c-f92702a99c48 · outbound

This paper cites Medical image registration: A review.Computer methods in biomechanics and biomedical engineering, 17:73–93, 01 2014.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Medical image registration: A review.Computer methods in biomechanics and biomedical engineering, 17:73–93, 01 2014

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:02.092080Z

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Observation ac102d96-e43e-4107-8451-0221f34db938 · outbound

This paper cites Fisp—a new fast mri sequence.Electromedica, 54(1):15–18, 1986.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Fisp—a new fast mri sequence.Electromedica, 54(1):15–18, 1986

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:01.927970Z

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Observation 6b6a9b47-c0d5-4d81-bf41-9455a60e6019 · outbound

This paper cites A review of deep learning in image recognition.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images A review of deep learning in image recognition

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Observation 583bfc2d-69c6-4ee9-9ba6-3c1b6647a858 · outbound

This paper cites Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration

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Observation c08f38c2-bb19-4c7b-89de-1602af96c741 · outbound

This paper cites Strain and strain rate echocardiography.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Strain and strain rate echocardiography

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:01.551660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8035c971-5c89-4a70-8dd9-1340e489ff7f · outbound

This paper cites Physics of mri: a primer.Journal of magnetic resonance imaging, 35(5):1038–1054, 2012.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Physics of mri: a primer.Journal of magnetic resonance imaging, 35(5):1038–1054, 2012

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:01.226683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1cc57e3b-ce7b-47d6-a683-ebf1dae1072d · outbound

This paper cites Cardiac magnetic resonance imaging: aone-stop-shop evaluation of myocardial dysfunction.Current opinion in cardiology, 17(6):663–670, 2002.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Cardiac magnetic resonance imaging: aone-stop-shop evaluation of myocardial dysfunction.Current opinion in cardiology, 17(6):663–670, 2002

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:01.002164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 342ce028-b4a6-4b00-ba3a-e4e8efc6bb04 · outbound

This paper cites End-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary mra.Magnetic Resonance in Medicine, 86(4):1983–1996, 2021.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images End-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary mra.Magnetic Resonance in Medicine, 86(4):1983–1996, 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:00.821748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b7fcbf8d-4111-40ce-9d06-b1d3279156bd · outbound

This paper cites 3-d facial expression represen- tation using b-spline statistical shape model.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images 3-d facial expression represen- tation using b-spline statistical shape model

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:00.557655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2fb1f315-0d7a-45b1-a2ac-f46148b010e1 · outbound

This paper cites Evaluating the potential of chelation therapy to prevent and treat gadolinium deposition from mri contrast agents.Scientic reports, 8(1):4419, 2018.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Evaluating the potential of chelation therapy to prevent and treat gadolinium deposition from mri contrast agents.Scientic reports, 8(1):4419, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:00.324626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 32452833-1050-4e36-a5d7-b8d1e9d84418 · outbound

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

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images U-net: Convolutional networks for biomedical image segmentation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:55.188104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987f3072-b9ff-4543-9a92-0630927fd912 · outbound

This paper cites Diagnostic and prognostic utility of cardiovascular magnetic resonance imaging in light-chain cardiac amyloidosis.The American journal of cardiology, 103(4):544– 549, 2009.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Diagnostic and prognostic utility of cardiovascular magnetic resonance imaging in light-chain cardiac amyloidosis.The American journal of cardiology, 103(4):544– 549, 2009

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:13:00.101498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ccc893e5-4f8f-45c6-bc49-96782dbecac3 · outbound

This paper cites Magnetization evo- lution in balanced steady-state free precession with continuously moving table.Physics in Medicine & Biology, 52(8):N173, 2007.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Magnetization evo- lution in balanced steady-state free precession with continuously moving table.Physics in Medicine & Biology, 52(8):N173, 2007

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:59.948533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 19a8d360-13a2-4fc8-ae9e-438cccc5846c · outbound

This paper cites Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.PLoS medicine, 12(3):e1001779, 2015.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.PLoS medicine, 12(3):e1001779, 2015

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:59.785596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ca13ff8-102d-46e8-b7ab-cb97861189b8 · outbound

This paper cites Introduction: The challenge of reinforcement learning.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Introduction: The challenge of reinforcement learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:59.547528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ea91ec71-1866-4d2a-9b7c-09dcce65fdfb · outbound

This paper cites Unsupervised machine learning for networking: Techniques, applications and research challenges.IEEE access, 7:65579–65615, 2019.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unsupervised machine learning for networking: Techniques, applications and research challenges.IEEE access, 7:65579–65615, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:59.322237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f223d03-c961-4917-a2c6-804321995929 · outbound

This paper cites A survey on semi-supervised learning.Machine learning, 109(2):373–440, 2020.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images A survey on semi-supervised learning.Machine learning, 109(2):373–440, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:55.532299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a865a3cd-44ed-438f-8444-52867471dad0 · outbound

This paper cites Principles of magnetic resonance imaging.Clinics in developmental medicine, pages 1–1, 1995.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Principles of magnetic resonance imaging.Clinics in developmental medicine, pages 1–1, 1995

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:59.104897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2f9b0ef1-f3b8-44c7-9f89-643abcaa341e · outbound

This paper cites Signicance of late gadolinium en- hancement in cardiovascular magnetic resonance imaging (cmr).HERZ-MUNICH-, 32(2):129, 2007.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Signicance of late gadolinium en- hancement in cardiovascular magnetic resonance imaging (cmr).HERZ-MUNICH-, 32(2):129, 2007

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:58.873900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c737323-f2dc-4b77-a4fa-c9e5a3b32752 · outbound

This paper cites Volumetric magnetic resonance imaging: clinical applications and contributions to the understanding of temporal lobe epilepsy.Archives of neurology, 54(12):1521–1531, 1997.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Volumetric magnetic resonance imaging: clinical applications and contributions to the understanding of temporal lobe epilepsy.Archives of neurology, 54(12):1521–1531, 1997

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:58.673857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6ed3fe9e-c855-4600-a9b8-0e24820088e4 · outbound

This paper cites Prog- nostic value of lge-cmr in hcm: a meta-analysis.JACC: Cardiovascular Imaging, 9(12):1392–1402, 2016.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Prog- nostic value of lge-cmr in hcm: a meta-analysis.JACC: Cardiovascular Imaging, 9(12):1392–1402, 2016

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:58.470924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 664bbb18-d83d-436b-bb14-74858a82589d · outbound

This paper cites an unresolved cited work.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-06T23:12:58.238891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f562dbcf-22ca-4662-b87c-2b3cc387bfdb · outbound

This paper cites Reluplex made more practical: Leaky relu.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Reluplex made more practical: Leaky relu

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:58.024881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 510d2c4b-8bfd-45a2-958a-d9bad075c43d · outbound

This paper cites Convolutional neural networks: an overview and application in radiology.Insights into imaging, 9:611–629, 2018.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Convolutional neural networks: an overview and application in radiology.Insights into imaging, 9:611–629, 2018

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation be3666ff-f222-4de3-87b3-9b424e35407e · outbound

This paper cites Quicksilver: Fast predictive image registration–a deep learning approach.NeuroImage, 158:378–396, 2017.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Quicksilver: Fast predictive image registration–a deep learning approach.NeuroImage, 158:378–396, 2017

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3095fecb-3549-45d4-a57d-c7dcc0d2caf7 · outbound

This paper cites Articial intelligence-based myocardial texture analysis in etiological dierentiation of left ventricular hypertrophy.Annals of Translational Medicine, 9(2), 2021.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Articial intelligence-based myocardial texture analysis in etiological dierentiation of left ventricular hypertrophy.Annals of Translational Medicine, 9(2), 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:57.452211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 69738bb5-1a7b-434a-b3bc-3145433abacc · outbound

This paper cites Motion artifacts in mri: A complex problem with many partial solutions.Journal of Magnetic Resonance Imaging, 42(4):887–901, 2015.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Motion artifacts in mri: A complex problem with many partial solutions.Journal of Magnetic Resonance Imaging, 42(4):887–901, 2015

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:57.272251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5c4c9ae4-bf3f-4acc-a9c7-f3f6e4916bca · outbound

This paper cites Fast and robust iterative closest point.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7):3450–3466, 2021.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Fast and robust iterative closest point.IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7):3450–3466, 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:57.060268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 315e4791-d7b1-4ea5-b138-53b9c2e5660a · outbound

This paper cites Recursive cascaded networks for unsupervised medical image registration.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Recursive cascaded networks for unsupervised medical image registration

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:56.926640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a1be5b82-76ad-4bb6-87ff-8a58e489f85c · outbound

This paper cites Unsupervised 3d end-to- end medical image registration with volume tweening network.IEEE journal of biomedical and health informatics, 24(5):1394–1404, 2019.

A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images Unsupervised 3d end-to- end medical image registration with volume tweening network.IEEE journal of biomedical and health informatics, 24(5):1394–1404, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:12:56.602443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Reference resolution

Outbound references

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