Keyword	Usage	Notes
Uploader	uploader: <uploader> , uploader: me	Keywords and values are case insensitive . "me" returns all the datasets that you uploaded.
Tags	tag: <tag 1> and <tag 2> , tags: <tag 1> and <tag 2> , tag: <tag 1>	Keywords and value are case insensitive. Inserting "and" will allow you to search for multiple tags. tags and tag are the same.
Project	project: <project name> ,	Keywords and value are case insensitive.
Anatomy	anatomy: <anatomy> ,	Keywords and value are case insensitive.
References	references: <references> , ref: <references>	Keywords and value are case insensitive. Ref and References are the same thing, but ref is a shortcut for references.
Comments	comments: <comment>	Keywords and value are case insensitive. Furthermore, it does NOT have to be an exact match, but rather if it contains.
Funding Support	funding_support: <supporter> , funding: <supporter> , support: <supporter> ,	Keywords and value are case insensitive. "funding" and "support" are both shortcuts for "funding_support".
System Vendor	system_vendor: <vendor> , vendor: <vendor>	Keywords and value are case insensitive. "vendor" is a shortcut for "system_vendor".
System Model	system_model: <model> , model: <model>	Keywords and value are case insensitive. "model" is a shortcut for "system_model".
Protocol Name	protocol_name: <protocol> , protocol: <protocol>	Keywords and value are case insensitive. "protocol" is a shortcut for "protocol_name".
Coil Name	coil_name: <coil> , coil: <coil>	Keywords and value are case insensitive. "coil" is a shortcut for "coil_name".
Sequence Type	sequence_type: <sequence> , sequence: <sequence>	Keywords and value are case insensitive. "sequence" is a shortcut for "sequence_type".
UUID	uuid: <uuid> , id: <uuid>	Keywords and value are case insensitive. "id" is a shortcut for "uuid".
Fully Sampled	fullysampled: <yes or no> , sampled: <yes or no>	Keywords and value are case insensitive. If sampled is unknown, state "unknown" or leave it blank. Response can also be "y" for "yes" and "n" for "no". Responses can also take the form of "1" for "yes" and "0" for "no". "sampled" is a shortcut for "fullysampled".

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

UUID	7d1e0fb6-0a43-4548-980c-4f0cdb20c367
Downloads	986
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 mm x 4.5 mm
Number of Averages	1
Number of Slices	42
Number of Phases	1
Number of Repetition	1
Number of Contrasts	1
Trajectory	cartesian
Parallel Imaging Factor	1.0 x 1.0
Repetition Time	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:43 a.m.

UUID	80c558dc-908f-4c64-84b0-e8e16da214c0
Downloads	990
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:42 a.m.

UUID	3dafaac6-e40a-45c3-a285-c88944e72dab
Downloads	1026
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:40 a.m.

UUID	fa9b7430-a024-4332-9913-9c56a0d941bf
Downloads	1012
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:39 a.m.

UUID	a0de6aae-7096-4cc7-bbb4-a4e4d159f680
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:38 a.m.

UUID	9d3c581f-0b10-446f-88ef-1b3014e400d6
Downloads	982
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:38 a.m.

UUID	cd255c11-ff09-4dd1-96e1-b7c5ed06f29c
Downloads	994
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:37 a.m.

UUID	9270505a-8d77-4e43-ac43-0d9910b81510
Downloads	970
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:36 a.m.

UUID	78d1ca02-a565-472d-bdc0-76450ade8cdf
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:35 a.m.

UUID	e1be2ec9-1934-463a-bc92-cfcb5b00031a
Downloads	983
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	COR
Series Description	COR
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 368 x 1
Field Of View	280 mm x 161.4 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	2750 ms
Echo Time	27 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	8.85 ms
Upload Date	Aug. 7, 2018, 6:35 a.m.

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