Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging | Paper Citation Record

Observation 8e025b4d-135f-415f-912d-9d7efe3f3f79 · outbound

This paper cites Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:17.039003Z

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Observation 5d09d160-521b-459d-a517-32bb5df0de97 · outbound

This paper cites Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:17.014125Z

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Observation be738c59-61c6-42c4-a5bf-9c0e2545d0c9 · outbound

This paper cites Compressed sensing based cone- beam computed tomography reconstruction with a ﬁrst-order method.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed sensing based cone- beam computed tomography reconstruction with a ﬁrst-order method

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.992269Z

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Observation 31b21a8e-88a8-44ca-b2de-b632ff479bbf · outbound

This paper cites Low-dose CT reconstruction via edge-preserving total variation regularization,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Low-dose CT reconstruction via edge-preserving total variation regularization,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.971771Z

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Observation 73fcb670-a82a-4472-97cd-52772bc90393 · outbound

This paper cites Compressed sens- ing for ultrasound computed tomography,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed sens- ing for ultrasound computed tomography,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.951693Z

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Observation b7762da9-b610-4430-bb5f-b7d02f159a1a · outbound

This paper cites Compressed sensing reconstruction of 3D ultrasound data using dictionary learning and line- wise subsampling,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed sensing reconstruction of 3D ultrasound data using dictionary learning and line- wise subsampling,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.935316Z

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Observation a398c573-492a-4369-97ae-f849d0c99880 · outbound

This paper cites Xampling in ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Xampling in ultrasound imaging,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.918278Z

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Observation 075ed637-756e-41a7-9741-1efb6f02613d · outbound

This paper cites Sparse MRI: The application of compressed sensing for rapid MR imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Sparse MRI: The application of compressed sensing for rapid MR imaging,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.901146Z

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Observation 88f1f198-87b7-4ead-bcbd-5bf4178e3dd0 · outbound

This paper cites Compressed sensing MRI,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed sensing MRI,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.884255Z

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Observation c3f66244-ae22-4798-ae4e-808327d76f98 · outbound

This paper cites Acuson freestyle series ultrasound systems,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Acuson freestyle series ultrasound systems,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.864830Z

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Observation b897d4b8-32ea-43f9-af31-a85e38fb9b7e · outbound

This paper cites Butterﬂy iq,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Butterﬂy iq,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.841769Z

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Observation e3785017-c5f0-4e47-81ad-4d738d87fc43 · outbound

This paper cites Ultrasound probe,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Ultrasound probe,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.821576Z

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Observation 138128f4-af09-4d73-be56-df3cce06148e · outbound

This paper cites 3D ultrafast ultrasound imaging in vivo,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging 3D ultrafast ultrasound imaging in vivo,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.801271Z

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Observation 5934b5f2-68ac-480a-a079-36167d671f67 · outbound

This paper cites Ultrafast imaging in biomedical ultrasound,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Ultrafast imaging in biomedical ultrasound,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.784406Z

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Observation aa5faa25-d9ad-4f7d-92dc-bedc7ce125f5 · outbound

This paper cites 2-D phased array ultrasound imaging system with distributed phasing,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging 2-D phased array ultrasound imaging system with distributed phasing,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.766768Z

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Observation eadc9fdf-92a4-4c59-a6c9-0f7c40461782 · outbound

This paper cites 4-D ice: A 2-D array transducer with integrated asic in a 10-fr catheter for real-time 3-D intracardiac echocardiography,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging 4-D ice: A 2-D array transducer with integrated asic in a 10-fr catheter for real-time 3-D intracardiac echocardiography,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.746314Z

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Observation 74958fd5-02f1-4e78-a134-01722da7c4a9 · outbound

This paper cites Stable signal recovery from incomplete and inaccurate measurements,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Stable signal recovery from incomplete and inaccurate measurements,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.729343Z

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Observation 8f54688e-9a3a-4978-9bc2-87171d6591cc · outbound

This paper cites Decoding by linear programming,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Decoding by linear programming,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.711360Z

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Observation 0a8802cb-1ec6-485d-b0d5-2560b9d09adf · outbound

This paper cites Compressive sampling,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressive sampling,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.693414Z

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Observation 2a02d247-071b-435d-b067-b4a0868ef619 · outbound

This paper cites Near-optimal signal recovery from random projections: Universal encoding strategies?.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Near-optimal signal recovery from random projections: Universal encoding strategies?

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.675939Z

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Observation 1764f316-975b-4544-8d44-5f3f483d0360 · outbound

This paper cites an unresolved cited work.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.509515Z

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Observation fffd7620-fce3-4582-9d65-e932aebbac13 · outbound

This paper cites The restricted isometry property and its implications for compressed sensing,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging The restricted isometry property and its implications for compressed sensing,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.646460Z

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Observation bb169956-5e8f-4f82-8d82-c470d300bf10 · outbound

This paper cites An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.523243Z

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Observation c751b693-ccf6-449a-b2eb-1e4116c62489 · outbound

This paper cites A deep learning approach to ultrasound image recovery,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging A deep learning approach to ultrasound image recovery,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.577231Z

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Observation 9d33ca57-9a6d-444c-99fe-ac1390a00818 · outbound

This paper cites Reconnet: Non-iterative recon- struction of images from compressively sensed measurements,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Reconnet: Non-iterative recon- struction of images from compressively sensed measurements,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.514164Z

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Observation 033940bd-75a0-4f73-96ec-429aaf493034 · outbound

This paper cites Categorical reparametrization with gumbel-softmax,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Categorical reparametrization with gumbel-softmax,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.476372Z

Source-reported events for the cited work

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Observation 3a21c268-be83-467a-aaab-fd2753c1450d · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.546364Z

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Observation 65db506d-7f3c-4072-a929-cc4aaeadbc99 · outbound

This paper cites Deep probabilistic subsampling for task-adaptive compressed sensing,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Deep probabilistic subsampling for task-adaptive compressed sensing,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.455167Z

Source-reported events for the cited work

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

Observation c94125e6-b735-4c33-b1ec-37b73b07456f · outbound

This paper cites k-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging k-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.433915Z

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Observation c3b08098-3740-4903-98ae-9bebf1ad1e57 · outbound

This paper cites Fourier-domain beamforming: the path to compressed ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Fourier-domain beamforming: the path to compressed ultrasound imaging,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.399263Z

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

Observation ff1b70f6-41d9-492d-8273-263e41f0cc51 · outbound

This paper cites A compressed beamforming framework for ultrafast ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging A compressed beamforming framework for ultrafast ultrasound imaging,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.376287Z

Source-reported events for the cited work

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

Observation 84681722-1d6d-475a-bd0f-9c2234c25438 · outbound

This paper cites Maximally economic sparse arrays and cantor arrays,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Maximally economic sparse arrays and cantor arrays,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.358562Z

Source-reported events for the cited work

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

Observation d5ac89bf-2233-4739-8efa-dc8237cec5c2 · outbound

This paper cites Sparse doppler sensing based on nested arrays,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Sparse doppler sensing based on nested arrays,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.338544Z

Source-reported events for the cited work

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

Observation 426801e2-6b16-46a6-b59f-3d20cbf2bc5f · outbound

This paper cites Sparse 2-D arrays for 3-D phased array imaging-design methods,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Sparse 2-D arrays for 3-D phased array imaging-design methods,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.317640Z

Source-reported events for the cited work

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

Observation 65edf56f-ba3d-4948-bf50-00abb6f50f56 · outbound

This paper cites Sparse convolutional beamforming for ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Sparse convolutional beamforming for ultrasound imaging,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.296299Z

Source-reported events for the cited work

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

Observation 5fe4f7e5-5452-4af3-9409-866af9ef2f5b · outbound

This paper cites A deep learning approach to structured signal recovery,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging A deep learning approach to structured signal recovery,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.277556Z

Source-reported events for the cited work

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

Observation 08846b2d-0cf5-4ae9-9b0c-ea7fd7fa5dc1 · outbound

This paper cites Learning to invert: Signal recovery via deep convolutional networks,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Learning to invert: Signal recovery via deep convolutional networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.258836Z

Source-reported events for the cited work

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

Observation 4bb8279b-9384-4299-8c96-e6854e82b4a1 · outbound

This paper cites Compressed Learning: A Deep Neural Network Approach.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Compressed Learning: A Deep Neural Network Approach

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.610759Z

Source-reported events for the cited work

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Observation c475c018-b5ae-4e1c-b525-c41e54653060 · outbound

This paper cites A Deep Learning Approach to Block-based Compressed Sensing of Images.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging A Deep Learning Approach to Block-based Compressed Sensing of Images

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.617454Z

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Observation bb489f8f-c66d-456b-809a-fdae956eebda · outbound

This paper cites ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:09:15.857001Z

Source-reported events for the cited work

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Observation 9a5acb5b-c7cc-417e-8204-516c97729be7 · outbound

This paper cites Statistical theory of extreme values and some practical applications,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Statistical theory of extreme values and some practical applications,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.239004Z

Source-reported events for the cited work

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

Observation 894d69c1-666e-405c-b1a9-522c20340164 · outbound

This paper cites Adam: A method for stochastic optimization,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Adam: A method for stochastic optimization,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.218916Z

Source-reported events for the cited work

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

Observation 1861b425-25f5-461a-950e-14ce9b2f7701 · outbound

This paper cites Keras: Deep learning library for theano and tensorﬂow,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Keras: Deep learning library for theano and tensorﬂow,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.198234Z

Source-reported events for the cited work

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

Observation 890c68d0-77b2-4dd2-b230-176234fcc12c · outbound

This paper cites Tensorﬂow: A system for large- scale machine learning,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Tensorﬂow: A system for large- scale machine learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.177263Z

Source-reported events for the cited work

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

Observation 70470bd8-46d4-4d76-b5f4-ed777c8ffe03 · outbound

This paper cites Combination of compressed sensing and parallel imaging for highly accelerated ﬁrst-pass cardiac perfusion MRI,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Combination of compressed sensing and parallel imaging for highly accelerated ﬁrst-pass cardiac perfusion MRI,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.157335Z

Source-reported events for the cited work

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

Observation 32f75d56-fc97-4ce3-8ddd-d613d0013810 · outbound

This paper cites Learning fast approximations of sparse coding,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Learning fast approximations of sparse coding,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.138253Z

Source-reported events for the cited work

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

Observation 8f77b840-7e57-43c8-b485-b65c833bbd01 · outbound

This paper cites Theoretical linear convergence of unfolded ista and its practical weights and thresholds,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Theoretical linear convergence of unfolded ista and its practical weights and thresholds,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.117613Z

Source-reported events for the cited work

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

Observation c0abcad6-0466-4f77-87f1-71b10d1ab319 · outbound

This paper cites Smooth sigmoid wavelet shrinkage for non-parametric estimation,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Smooth sigmoid wavelet shrinkage for non-parametric estimation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.098644Z

Source-reported events for the cited work

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

Observation abe44def-ff4b-486e-bf6e-2838703164ad · outbound

This paper cites Learning Doppler with deep neural networks and its application to intra-cardiac echography,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Learning Doppler with deep neural networks and its application to intra-cardiac echography,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.078809Z

Source-reported events for the cited work

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

Observation 29b48cab-10ff-458d-a344-d90c2145edbe · outbound

This paper cites Deep learning in ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Deep learning in ultrasound imaging,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.059147Z

Source-reported events for the cited work

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

Observation b5ff6d91-8d24-4f50-97e5-ba02548af671 · outbound

This paper cites Real-time two-dimensional blood ﬂow imaging using an autocorrelation technique,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Real-time two-dimensional blood ﬂow imaging using an autocorrelation technique,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.040846Z

Source-reported events for the cited work

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

Observation 7f57ca2e-1fb6-4f6a-b3fb-26fa8d4ae2df · outbound

This paper cites Goodfellow, Y.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Goodfellow, Y

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.697018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a4ac0c3-5173-480f-bbca-45c76cd84b67 · outbound

This paper cites Empirical Evaluation of Rectified Activations in Convolutional Network.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Empirical Evaluation of Rectified Activations in Convolutional Network

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.702444Z

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Unavailable: canonical work link unavailable.

Observation 4db0918d-2f32-464f-9dbc-fc0943c7c2c8 · outbound

This paper cites High-frame-rate echocardiography using diverging transmit beams and parallel receive beamforming,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging High-frame-rate echocardiography using diverging transmit beams and parallel receive beamforming,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:16.005241Z

Source-reported events for the cited work

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

Observation cd2cf433-1147-47a4-9d52-07e78b657304 · outbound

This paper cites an unresolved cited work.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:09:15.984524Z

Source-reported events for the cited work

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

Observation 4792fa8f-8cce-480a-b474-14f1aa43a16e · outbound

This paper cites Deep image prior,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Deep image prior,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:15.967144Z

Source-reported events for the cited work

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

Observation 66d040d2-bdc8-4936-8717-80f139579b87 · outbound

This paper cites Deep learning for fast adaptive beamforming,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Deep learning for fast adaptive beamforming,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:15.948498Z

Source-reported events for the cited work

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

Observation 887406b4-9fa9-4c5f-9e18-576385981ea6 · outbound

This paper cites Adaptive Ultrasound Beamforming using Deep Learning.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Adaptive Ultrasound Beamforming using Deep Learning

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:09:15.808072Z

Source-reported events for the cited work

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

Observation ffe24c14-784d-416b-8d07-6691e38eedcf · outbound

This paper cites Super- resolution ultrasound imaging,.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Super- resolution ultrasound imaging,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:09:15.929344Z

Source-reported events for the cited work

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

Observation a5797f88-4891-4857-a78f-f70d9223039d · outbound

This paper cites Super-resolution Ultrasound Localization Microscopy through Deep Learning.

Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging Super-resolution Ultrasound Localization Microscopy through Deep Learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-14T13:09:15.741892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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