Self-supervised feature learning for cardiac Cine MR image reconstruction | Paper Citation Record

Observation 1e4da0db-e598-4e30-b34d-e8641b2fc76a · outbound

This paper cites SENSE: sensitivity encoding for fast MRI,.

Self-supervised feature learning for cardiac Cine MR image reconstruction SENSE: sensitivity encoding for fast MRI,

Reference 1

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Observation 89b5d247-a6c2-41a6-b854-0feefd05e9e4 · outbound

This paper cites Generalized autocalibrating partially parallel acquisitions (GRAPPA),.

Self-supervised feature learning for cardiac Cine MR image reconstruction Generalized autocalibrating partially parallel acquisitions (GRAPPA),

Reference 2

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This paper cites SPIRiT: iterative self-cons istent parallel imaging reconstruction from arbitrary k-space,.

Self-supervised feature learning for cardiac Cine MR image reconstruction SPIRiT: iterative self-cons istent parallel imaging reconstruction from arbitrary k-space,

Reference 3

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Observation bfeae1e2-8bd6-4ae1-9bcc-d28fc1576e2e · outbound

This paper cites ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA.,.

Self-supervised feature learning for cardiac Cine MR image reconstruction ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA.,

Reference 4

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This paper cites A wavelet-based regularized reconstruction algorithm for S ENSE parallel MRI with applications to neuroimaging,.

Self-supervised feature learning for cardiac Cine MR image reconstruction A wavelet-based regularized reconstruction algorithm for S ENSE parallel MRI with applications to neuroimaging,

Reference 5

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This paper cites An ite rative regu- larization method for total variation-based image restora tion,.

Self-supervised feature learning for cardiac Cine MR image reconstruction An ite rative regu- larization method for total variation-based image restora tion,

Reference 6

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This paper cites Undersampled radia l MRI with multiple coils. Iterative image reconstruction using a total variation constraint,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Undersampled radia l MRI with multiple coils. Iterative image reconstruction using a total variation constraint,

Reference 7

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Observation d0a6470e-0944-450a-a95b-d79bdccf1c42 · outbound

This paper cites Ada ptive dictionary learning in sparse gradient domain for image rec overy,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Ada ptive dictionary learning in sparse gradient domain for image rec overy,

Reference 8

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Observation dd6899a3-7f8e-4e4f-91fa-d0ad335baafc · outbound

This paper cites Dictionary learning and time sparsity for dynamic MR data reconstructi on,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Dictionary learning and time sparsity for dynamic MR data reconstructi on,

Reference 9

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This paper cites Reconstruction with dictionary learning f or accelerated parallel magnetic resonance imaging,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Reconstruction with dictionary learning f or accelerated parallel magnetic resonance imaging,

Reference 10

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Observation 8ebe4af0-f344-4115-b2fe-3b030f30ba2d · outbound

This paper cites SparseSENSE: applicatio n of compressed sensing in parallel MRI,.

Self-supervised feature learning for cardiac Cine MR image reconstruction SparseSENSE: applicatio n of compressed sensing in parallel MRI,

Reference 11

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This paper cites Accel eration of MR parameter mapping using annihilating ﬁlter-based low ra nk hankel matrix (ALOHA),.

Self-supervised feature learning for cardiac Cine MR image reconstruction Accel eration of MR parameter mapping using annihilating ﬁlter-based low ra nk hankel matrix (ALOHA),

Reference 12

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This paper cites Scan-speciﬁc robust artiﬁcial-neural-networks for k-space interpolat ion (RAKI) recon- struction: Database-free deep learning for fast imaging,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Scan-speciﬁc robust artiﬁcial-neural-networks for k-space interpolat ion (RAKI) recon- struction: Database-free deep learning for fast imaging,

Reference 13

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Observation c9f6ca7b-2790-448b-a4de-af160694d304 · outbound

This paper cites Deep residual learni ng for accelerated MRI using magnitude and phase networks,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Deep residual learni ng for accelerated MRI using magnitude and phase networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:52:38.533644Z

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This paper cites Real-time cardiovascular MR with spatio-temporal artifa ct suppression using deep learning–proof of concept in congenital heart di sease,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Real-time cardiovascular MR with spatio-temporal artifa ct suppression using deep learning–proof of concept in congenital heart di sease,

Reference 15

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Observation 58a53872-898a-40e8-b8b3-8a1c94754c40 · outbound

This paper cites Spatio- temporal deep learning-based undersampling artefact redu ction for 2D radial cine MRI with limited training data,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Spatio- temporal deep learning-based undersampling artefact redu ction for 2D radial cine MRI with limited training data,

Reference 16

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This paper cites A deep cascade of convolutional neural networks for dynamic M R image reconstruction,.

Self-supervised feature learning for cardiac Cine MR image reconstruction A deep cascade of convolutional neural networks for dynamic M R image reconstruction,

Reference 17

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Observation ce8f9b4a-7d11-4eeb-8d4f-e0fa039eb50f · outbound

This paper cites Learning a variational network for reconstruction of accelerated MRI data,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Learning a variational network for reconstruction of accelerated MRI data,

Reference 18

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Observation 1f44fcf4-39d3-4a50-9a15-1d46e0d19ec9 · outbound

This paper cites CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spat io-temporal convolutions,.

Self-supervised feature learning for cardiac Cine MR image reconstruction CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spat io-temporal convolutions,

Reference 19

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Observation d59f0718-e354-4c1a-ba8c-d93cc916e2ce · outbound

This paper cites KIK I-net: cross-domain convolutional neural networks for reconstru cting under- sampled magnetic resonance images,.

Self-supervised feature learning for cardiac Cine MR image reconstruction KIK I-net: cross-domain convolutional neural networks for reconstru cting under- sampled magnetic resonance images,

Reference 20

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Observation 1af5a421-c5cc-49e5-98eb-577995da76de · outbound

This paper cites Multi-domain convolutional neural network (MD- CNN) for radial reconstruction of dynamic cardiac MRI,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Multi-domain convolutional neural network (MD- CNN) for radial reconstruction of dynamic cardiac MRI,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:52:37.138504Z

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Observation 9a9b50a9-e834-4631-9b39-cebc16cd51f2 · outbound

This paper cites Knowledge-driven deep learning for fast MR imaging: Under sampled MR image reconstruction from supervised to un-supervised l earning.

Self-supervised feature learning for cardiac Cine MR image reconstruction Knowledge-driven deep learning for fast MR imaging: Under sampled MR image reconstruction from supervised to un-supervised l earning

Reference 22

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Observation 11dbccd2-996b-45c0-a8a3-105eddca584e · outbound

This paper cites A review on deep learning MRI reconstruction without fully sampled k-space.

Self-supervised feature learning for cardiac Cine MR image reconstruction A review on deep learning MRI reconstruction without fully sampled k-space

Reference 23

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Observation 16657a83-9fa9-430c-b71a-40704ebe2525 · outbound

This paper cites Deep learning for accelerated and robust MRI reconstruction.

Self-supervised feature learning for cardiac Cine MR image reconstruction Deep learning for accelerated and robust MRI reconstruction

Reference 24

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Observation 91d45261-f184-4077-9d6d-df4d6e4b3527 · outbound

This paper cites On instabilities of deep learning in image reconstruction and the potential 12 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. XX, NO. XX, XXX X 2020 costs of AI.

Self-supervised feature learning for cardiac Cine MR image reconstruction On instabilities of deep learning in image reconstruction and the potential 12 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. XX, NO. XX, XXX X 2020 costs of AI

Reference 25

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Observation 6b39f0a0-de23-4bad-b2c6-3a9d481afd86 · outbound

This paper cites Self-supervised learning of physics-gu ided recon- struction neural networks without fully sampled reference data,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Self-supervised learning of physics-gu ided recon- struction neural networks without fully sampled reference data,

Reference 26

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Observation 991f10c4-366a-4cb6-9562-b81c9f26a382 · outbound

This paper cites Multi-mask self-supervised learning for physics- guided neural networks in highly accelerated magnetic reso nance imag- ing,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Multi-mask self-supervised learning for physics- guided neural networks in highly accelerated magnetic reso nance imag- ing,

Reference 27

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This paper cites A theoretical framework for s elf-supervised MR image reconstruction using sub-sampling via variable de nsity Nois- ier2Noise.

Self-supervised feature learning for cardiac Cine MR image reconstruction A theoretical framework for s elf-supervised MR image reconstruction using sub-sampling via variable de nsity Nois- ier2Noise

Reference 28

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Observation b76c0f74-8783-4495-9389-35020bd445f3 · outbound

This paper cites Noisier2n oise: Learn- ing to denoise from unpaired noisy data.

Self-supervised feature learning for cardiac Cine MR image reconstruction Noisier2n oise: Learn- ing to denoise from unpaired noisy data

Reference 29

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Observation 5b1a5fd5-4d49-4c5c-8519-ac39cb9a5e99 · outbound

This paper cites Dual-domain self-supervised learning for accelerated non-cartesian mri reconstruction,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Dual-domain self-supervised learning for accelerated non-cartesian mri reconstruction,

Reference 30

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Observation c3f59031-1d59-4555-b96f-5368f6420bdd · outbound

This paper cites Noise2Recon: Enabling SNR-robust MRI recon- struction with semi-supervised and self-supervised learn ing,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Noise2Recon: Enabling SNR-robust MRI recon- struction with semi-supervised and self-supervised learn ing,

Reference 31

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Observation 74b55dd5-b2b5-430a-a812-90f1ba4986d1 · outbound

This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Self-supervised feature learning for cardiac Cine MR image reconstruction Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 32

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This paper cites Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction.

Self-supervised feature learning for cardiac Cine MR image reconstruction Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction

Reference 33

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This paper cites Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data.

Self-supervised feature learning for cardiac Cine MR image reconstruction Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data

Reference 34

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Observation dc816ffd-ae1b-4dec-91d9-c12c9d8a5267 · outbound

This paper cites Learning re presentations by maximizing mutual information across views,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Learning re presentations by maximizing mutual information across views,

Reference 35

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Observation 121708dc-a383-4397-a819-6f9b75180258 · outbound

This paper cites Momentum co ntrast for unsupervised visual representation learning,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Momentum co ntrast for unsupervised visual representation learning,

Reference 36

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This paper cites Exploring simple siamese represent ation learning,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Exploring simple siamese represent ation learning,

Reference 37

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Observation 9f95834e-f3e5-4273-9cc0-0c42fae8b432 · outbound

This paper cites VICReg: variance-in variance- covariance regularization for self-supervised learning,.

Self-supervised feature learning for cardiac Cine MR image reconstruction VICReg: variance-in variance- covariance regularization for self-supervised learning,

Reference 38

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Observation 6f907214-d2b4-44c9-a647-d67e5dc49c30 · outbound

This paper cites Signature veriﬁcation using a.

Self-supervised feature learning for cardiac Cine MR image reconstruction Signature veriﬁcation using a

Reference 39

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This paper cites A simp le frame- work for contrastive learning of visual representations,.

Self-supervised feature learning for cardiac Cine MR image reconstruction A simp le frame- work for contrastive learning of visual representations,

Reference 40

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This paper cites Bar low twins: Self-supervised learning via redundancy reduction,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Bar low twins: Self-supervised learning via redundancy reduction,

Reference 41

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This paper cites A review of self-supervised, generative, and fe w-shot deep learning methods for data-limited magnetic resonance imaging segmentation,.

Self-supervised feature learning for cardiac Cine MR image reconstruction A review of self-supervised, generative, and fe w-shot deep learning methods for data-limited magnetic resonance imaging segmentation,

Reference 42

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This paper cites PARCEL: physics-based unsupervised contrastive representation learning for multi-coil MR imaging,.

Self-supervised feature learning for cardiac Cine MR image reconstruction PARCEL: physics-based unsupervised contrastive representation learning for multi-coil MR imaging,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:58.563261Z

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Observation 0fa6d8a7-496b-4301-9a53-21969b4eee08 · outbound

This paper cites Contrastive Learning for Local and Global Learning MRI Reconstruction.

Self-supervised feature learning for cardiac Cine MR image reconstruction Contrastive Learning for Local and Global Learning MRI Reconstruction

Reference 44

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Observation 9dde7328-e41a-4fa3-9ec2-e367c84cebba · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Self-supervised feature learning for cardiac Cine MR image reconstruction Representation Learning with Contrastive Predictive Coding

Reference 45

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Observation 795a9c4c-8ba5-4b94-a5ba-de7f53aff277 · outbound

This paper cites Unitary evolution recurrent neural networks,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Unitary evolution recurrent neural networks,

Reference 46

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Observation 40a99924-a981-4963-a5fb-2f54d0215aa7 · outbound

This paper cites V ariable density incoherent spatiotemporal acquisition (VISTA) for highly accelerated cardiac MRI,.

Self-supervised feature learning for cardiac Cine MR image reconstruction V ariable density incoherent spatiotemporal acquisition (VISTA) for highly accelerated cardiac MRI,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:58.222217Z

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Observation fcfc887b-fc79-436c-b214-52d76a5dc9ad · outbound

This paper cites OCMR (v1.0)--Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging.

Self-supervised feature learning for cardiac Cine MR image reconstruction OCMR (v1.0)--Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging

Reference 48

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Observation 262fbbc5-2240-4e4e-9bef-082f119c4d3d · outbound

This paper cites Machine enhanced recon struction learning and interpretation networks (MERLIN),.

Self-supervised feature learning for cardiac Cine MR image reconstruction Machine enhanced recon struction learning and interpretation networks (MERLIN),

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:58.011260Z

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Observation bfe3332b-88f0-4d9b-95f3-18dc68670873 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Self-supervised feature learning for cardiac Cine MR image reconstruction Adam: A Method for Stochastic Optimization

Reference 50

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Observation 3d4268f1-3980-4071-b007-621074af1325 · outbound

This paper cites Accelera ted dynamic MRI exploiting sparsity and low-rank structure: kt SLR,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Accelera ted dynamic MRI exploiting sparsity and low-rank structure: kt SLR,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:57.831679Z

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Observation 8d41c926-c67e-4367-80b2-916b422a1be7 · outbound

This paper cites Learning- based optimization of the under-sampling pattern in MRI,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Learning- based optimization of the under-sampling pattern in MRI,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:57.610399Z

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Observation fdbe186e-ad01-4311-866c-f79d9710c77b · outbound

This paper cites Fast data -driven learning of parallel MRI sampling patterns for large scale p roblems,.

Self-supervised feature learning for cardiac Cine MR image reconstruction Fast data -driven learning of parallel MRI sampling patterns for large scale p roblems,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:51:57.376514Z

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