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	edb3e7ff-463c-433e-94cf-700ed004365e
Downloads	898
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	44
Number of Phases	1
Number of Repetition	1
Number of Contrasts	1
Trajectory	cartesian
Parallel Imaging Factor	1.0 x 1.0
Repetition Time	3480 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:45 p.m.

UUID	721b2fa6-2500-4b24-be9f-312d9627119e
Downloads	903
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	2870 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:44 p.m.

UUID	9d4b66ea-e3db-4ea8-b3a8-1e6c2642e6d9
Downloads	893
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	37
Number of Phases	1
Number of Repetition	1
Number of Contrasts	1
Trajectory	cartesian
Parallel Imaging Factor	1.0 x 1.0
Repetition Time	2930 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:43 p.m.

UUID	c01e98cd-e697-417e-ba10-ee6ed44cd1fa
Downloads	913
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	37
Number of Phases	1
Number of Repetition	1
Number of Contrasts	1
Trajectory	cartesian
Parallel Imaging Factor	1.0 x 1.0
Repetition Time	2930 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:40 p.m.

UUID	0e4365a8-a975-437a-95f4-35bcde5da5f1
Downloads	921
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	3010 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:38 p.m.

UUID	3578cd98-650c-4489-884e-7e162202b961
Downloads	922
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	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	2870 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:37 p.m.

UUID	3b9624fd-87dc-4b52-a348-65b883797c13
Downloads	876
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	37
Number of Phases	1
Number of Repetition	1
Number of Contrasts	1
Trajectory	cartesian
Parallel Imaging Factor	1.0 x 1.0
Repetition Time	2930 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:36 p.m.

UUID	9a4547c6-ff93-480b-a6e7-ed7300e1af60
Downloads	875
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	2870 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:33 p.m.

UUID	cb6b0a02-7a18-4676-884d-7668e609e351
Downloads	894
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	3010 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:30 p.m.

UUID	e12bd02b-6456-4d31-8b01-c3b7843da0a6
Downloads	899
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	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	2870 ms
Echo Time	33 ms
Inversion Time	100 ms
Flip Angle	180 °
Sequence Type	TurboSpinEcho
Echo Spacing	10.96 ms
Upload Date	Aug. 6, 2018, 12:28 p.m.

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