Total 247 datasets Download UUIDs
Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID cafc2ace-a826-4344-8cf9-896ec8bc6120
Downloads 79
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 676 x 1
Field Of View 280 mm x 246.1 mm x 4.5 mm
Number of Averages 1
Number of Slices 38
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 7:03 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID 936c76f0-b3af-41f0-9b2d-f468f6a71225
Downloads 79
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 33
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 7:02 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID e5bea69e-3b5e-44e9-9307-c182b8caf6db
Downloads 82
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 35
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 7:01 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID 7953af76-63f4-4b64-984a-adbc67ade280
Downloads 74
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 33
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 7 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID cc52722b-8649-45b0-a1ea-8727c1687ad5
Downloads 75
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 36
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:58 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID 18fe726f-1085-4c93-989b-0f79f084fbe4
Downloads 77
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 31
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:57 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID 907e4462-c45d-4a62-8ade-553f2c217312
Downloads 73
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 38
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:56 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID af169293-1b83-4bd9-a8cf-4708325cdf73
Downloads 74
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 35
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:54 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID c22a01be-8903-4ad3-b58d-3781b2d20bf8
Downloads 69
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 31
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:52 a.m.

Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll

UUID 3b2f97c1-6c7a-41b7-82bb-698f0b6fd3d0
Downloads 75
References Hammernik K, Klatzer T, Kobler E, Recht M, Sodickson D, Pock T, Knoll F. Learning a Variational Network for Reconstruction of Accelerated MRI Data. Magnetic Resonance in Medicine 79: 3055–3071 (2018)
Comments This is part of the training and test data that was used for our 2017 MRM manuscript on learning a variational network to reconstruct accelerated MR data. The data accompanies the code repository at: https://github.com/VLOGroup/mri-variationalnetwork.
Funding Support NIH P41 EB017183
Protocol Name SAG
Series Description SAG
System Vendor SIEMENS
System Model Skyra
System Field Strength 2.89362 T
Receiver Bandwidth 0.793
Number of Channels 15
Coil Name TxRx_15Ch_Knee:1:K5
Institution Name HJD
Matrix Size 768 x 770 x 1
Field Of View 280 mm x 280.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 34
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 2800 ms
Echo Time 22 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 8, 2018, 6:51 a.m.

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