Total 249 datasets
Project: NYU machine learning data
Anatomy: Knee
Fullysampled: Yes
Uploader: florianknoll
Tags:

UUID af169293-1b83-4bd9-a8cf-4708325cdf73
Downloads 987
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
Tags:

UUID c22a01be-8903-4ad3-b58d-3781b2d20bf8
Downloads 979
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
Tags:

UUID 3b2f97c1-6c7a-41b7-82bb-698f0b6fd3d0
Downloads 998
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.

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

UUID 36ddbca0-c5fd-41a3-854d-4790649d89c2
Downloads 864
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 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 4000 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:06 a.m.

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

UUID c155c00a-80af-421b-ae48-e7ed0dec9777
Downloads 877
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 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 4000 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:05 a.m.

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

UUID d65e98c1-f893-48b5-b093-057b327a410c
Downloads 813
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 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 4260 ms
Echo Time 67 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 11.12 ms
Upload Date Aug. 7, 2018, 11:04 a.m.

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

UUID 3c8b5e73-29ab-400d-b397-5f0bca4b7cb6
Downloads 840
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 39
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 4100 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:03 a.m.

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

UUID 34c9860c-c752-4062-aaf5-530d63272c98
Downloads 835
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 40
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 4210 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:03 a.m.

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

UUID 47a37b36-d970-47b4-ac8c-3b2c8d50d002
Downloads 829
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 mm x 4.5 mm
Number of Averages 1
Number of Slices 41
Number of Phases 1
Number of Repetition 1
Number of Contrasts 1
Trajectory cartesian
Parallel Imaging Factor 1.0 x 1.0
Repetition Time 4310 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:02 a.m.

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

UUID 2448503f-4fda-4e3e-b269-bfffa814962d
Downloads 851
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 AX
Series Description AX
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 640 x 484 x 1
Field Of View 280 mm x 211.7 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 4000 ms
Echo Time 65 ms
Inversion Time 100 ms
Flip Angle 150 °
Sequence Type TurboSpinEcho
Echo Spacing 9.33 ms
Upload Date Aug. 7, 2018, 11:01 a.m.

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