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

UUID 413469fd-9354-400c-88e3-b29e7c711a05
Downloads 87
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, 7:12 a.m.

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

UUID 6a8fff64-9bba-4ce7-aa58-d024214b4d7a
Downloads 178
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, 7:12 a.m.

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

UUID bd01dd30-46e7-4415-bf04-ed4cc6ac2b64
Downloads 41
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, 7:11 a.m.

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

UUID 6493682f-c9d3-44a7-8c0f-7fdf8b165410
Downloads 43
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, 7:10 a.m.

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

UUID 48c95dcf-c074-499b-a63c-74f0bf7dff1f
Downloads 39
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 32
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, 7:09 a.m.

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

UUID de6d23d9-b1c4-46af-bc79-ce828f5cd63a
Downloads 38
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, 7:08 a.m.

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

UUID e3573a0f-34f7-4718-827a-027bf9dd4dea
Downloads 35
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 672 x 1
Field Of View 280 mm x 245.1 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 2.0 x 1.0
Repetition Time 2300 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, 7:07 a.m.

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

UUID a496da39-848a-4fe8-8954-ff63df6785cb
Downloads 34
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 768 x 1
Field Of View 280 mm x 280.3 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 2.0 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, 7:07 a.m.

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

UUID 516288da-d22b-4e92-9282-96665134c84a
Downloads 41
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 32
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, 7:06 a.m.

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

UUID 90bc0b15-eea2-4abb-b0d2-f3fdad57bb43
Downloads 38
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, 7:05 a.m.

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