Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging

Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system...
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Autor*in:	Dan Wu [verfasserIn] Liyi Kang [verfasserIn] Haotian Li [verfasserIn] Ruicheng Ba [verfasserIn] Zuozhen Cao [verfasserIn] Qian Liu [verfasserIn] Yingchao Tan [verfasserIn] Qinwei Zhang [verfasserIn] Bo Li [verfasserIn] Jianmin Yuan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping

Übergeordnetes Werk:	In: NeuroImage - Elsevier, 2020, 290(2024), Seite 120553-
Übergeordnetes Werk:	volume:290 ; year:2024 ; pages:120553-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.neuroimage.2024.120553

Katalog-ID:	DOAJ097106917

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spelling	10.1016/j.neuroimage.2024.120553 doi (DE-627)DOAJ097106917 (DE-599)DOAJ9cbd5a3129a64fceae85bf55e4c40b38 DE-627 ger DE-627 rakwb eng RC321-571 Dan Wu verfasserin aut Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches. Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping Neurosciences. Biological psychiatry. Neuropsychiatry Liyi Kang verfasserin aut Haotian Li verfasserin aut Ruicheng Ba verfasserin aut Zuozhen Cao verfasserin aut Qian Liu verfasserin aut Yingchao Tan verfasserin aut Qinwei Zhang verfasserin aut Bo Li verfasserin aut Jianmin Yuan verfasserin aut In NeuroImage Elsevier, 2020 290(2024), Seite 120553- (DE-627)268125503 (DE-600)1471418-8 10959572 nnns volume:290 year:2024 pages:120553- https://doi.org/10.1016/j.neuroimage.2024.120553 kostenfrei https://doaj.org/article/9cbd5a3129a64fceae85bf55e4c40b38 kostenfrei http://www.sciencedirect.com/science/article/pii/S105381192400048X kostenfrei https://doaj.org/toc/1095-9572 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 290 2024 120553-
allfields_unstemmed	10.1016/j.neuroimage.2024.120553 doi (DE-627)DOAJ097106917 (DE-599)DOAJ9cbd5a3129a64fceae85bf55e4c40b38 DE-627 ger DE-627 rakwb eng RC321-571 Dan Wu verfasserin aut Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches. Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping Neurosciences. Biological psychiatry. Neuropsychiatry Liyi Kang verfasserin aut Haotian Li verfasserin aut Ruicheng Ba verfasserin aut Zuozhen Cao verfasserin aut Qian Liu verfasserin aut Yingchao Tan verfasserin aut Qinwei Zhang verfasserin aut Bo Li verfasserin aut Jianmin Yuan verfasserin aut In NeuroImage Elsevier, 2020 290(2024), Seite 120553- (DE-627)268125503 (DE-600)1471418-8 10959572 nnns volume:290 year:2024 pages:120553- https://doi.org/10.1016/j.neuroimage.2024.120553 kostenfrei https://doaj.org/article/9cbd5a3129a64fceae85bf55e4c40b38 kostenfrei http://www.sciencedirect.com/science/article/pii/S105381192400048X kostenfrei https://doaj.org/toc/1095-9572 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 290 2024 120553-
allfieldsGer	10.1016/j.neuroimage.2024.120553 doi (DE-627)DOAJ097106917 (DE-599)DOAJ9cbd5a3129a64fceae85bf55e4c40b38 DE-627 ger DE-627 rakwb eng RC321-571 Dan Wu verfasserin aut Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches. Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping Neurosciences. Biological psychiatry. Neuropsychiatry Liyi Kang verfasserin aut Haotian Li verfasserin aut Ruicheng Ba verfasserin aut Zuozhen Cao verfasserin aut Qian Liu verfasserin aut Yingchao Tan verfasserin aut Qinwei Zhang verfasserin aut Bo Li verfasserin aut Jianmin Yuan verfasserin aut In NeuroImage Elsevier, 2020 290(2024), Seite 120553- (DE-627)268125503 (DE-600)1471418-8 10959572 nnns volume:290 year:2024 pages:120553- https://doi.org/10.1016/j.neuroimage.2024.120553 kostenfrei https://doaj.org/article/9cbd5a3129a64fceae85bf55e4c40b38 kostenfrei http://www.sciencedirect.com/science/article/pii/S105381192400048X kostenfrei https://doaj.org/toc/1095-9572 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 290 2024 120553-
allfieldsSound	10.1016/j.neuroimage.2024.120553 doi (DE-627)DOAJ097106917 (DE-599)DOAJ9cbd5a3129a64fceae85bf55e4c40b38 DE-627 ger DE-627 rakwb eng RC321-571 Dan Wu verfasserin aut Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches. Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping Neurosciences. Biological psychiatry. Neuropsychiatry Liyi Kang verfasserin aut Haotian Li verfasserin aut Ruicheng Ba verfasserin aut Zuozhen Cao verfasserin aut Qian Liu verfasserin aut Yingchao Tan verfasserin aut Qinwei Zhang verfasserin aut Bo Li verfasserin aut Jianmin Yuan verfasserin aut In NeuroImage Elsevier, 2020 290(2024), Seite 120553- (DE-627)268125503 (DE-600)1471418-8 10959572 nnns volume:290 year:2024 pages:120553- https://doi.org/10.1016/j.neuroimage.2024.120553 kostenfrei https://doaj.org/article/9cbd5a3129a64fceae85bf55e4c40b38 kostenfrei http://www.sciencedirect.com/science/article/pii/S105381192400048X kostenfrei https://doaj.org/toc/1095-9572 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 290 2024 120553-
language	English
source	In NeuroImage 290(2024), Seite 120553- volume:290 year:2024 pages:120553-
sourceStr	In NeuroImage 290(2024), Seite 120553- volume:290 year:2024 pages:120553-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping Neurosciences. Biological psychiatry. Neuropsychiatry
isfreeaccess_bool	true
container_title	NeuroImage
authorswithroles_txt_mv	Dan Wu @@aut@@ Liyi Kang @@aut@@ Haotian Li @@aut@@ Ruicheng Ba @@aut@@ Zuozhen Cao @@aut@@ Qian Liu @@aut@@ Yingchao Tan @@aut@@ Qinwei Zhang @@aut@@ Bo Li @@aut@@ Jianmin Yuan @@aut@@
publishDateDaySort_date	2024-01-01T00:00:00Z
hierarchy_top_id	268125503
id	DOAJ097106917
language_de	englisch
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callnumber-first	R - Medicine
author	Dan Wu
spellingShingle	Dan Wu misc RC321-571 misc Neuroscience misc Ultra-high gradient misc High-resolution misc AI-assisted compressed sensing misc Diffusion MRI misc Microstructural mapping misc Neurosciences. Biological psychiatry. Neuropsychiatry Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging
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topic_title	RC321-571 Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging Neuroscience Ultra-high gradient High-resolution AI-assisted compressed sensing Diffusion MRI Microstructural mapping
topic	misc RC321-571 misc Neuroscience misc Ultra-high gradient misc High-resolution misc AI-assisted compressed sensing misc Diffusion MRI misc Microstructural mapping misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_unstemmed	misc RC321-571 misc Neuroscience misc Ultra-high gradient misc High-resolution misc AI-assisted compressed sensing misc Diffusion MRI misc Microstructural mapping misc Neurosciences. Biological psychiatry. Neuropsychiatry
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title	Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging
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title_full	Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging
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author_browse	Dan Wu Liyi Kang Haotian Li Ruicheng Ba Zuozhen Cao Qian Liu Yingchao Tan Qinwei Zhang Bo Li Jianmin Yuan
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title_sort	developing an ai-empowered head-only ultra-high-performance gradient mri system for high spatiotemporal neuroimaging
callnumber	RC321-571
title_auth	Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging
abstract	Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
abstractGer	Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
abstract_unstemmed	Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
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title_short	Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging
url	https://doi.org/10.1016/j.neuroimage.2024.120553 https://doaj.org/article/9cbd5a3129a64fceae85bf55e4c40b38 http://www.sciencedirect.com/science/article/pii/S105381192400048X https://doaj.org/toc/1095-9572
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Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging

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