Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jingyu Ko"'
Publikováno v:
European Radiology. 32:5468-5479
This study aimed to accelerate the 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence for brain imaging through the deep neural network (DNN).This retrospective study used the k-space data of 240 scans (160 for the training set, mean ±
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99f0f96c243ecc787066d9c8a8f2289a
https://doi.org/10.1007/s00330-022-08687-6
https://doi.org/10.1007/s00330-022-08687-6
Publikováno v:
The British Journal of Radiology. 95
Objective: The aim of this study was to develop a deep neural network (DNN)-based parallel imaging reconstruction for highly accelerated 2D turbo spin echo (TSE) data in prostate MRI without quality degradation compared to conventional scans. Methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f33a78a88795336df40ab7c434b8766
https://doi.org/10.1259/bjr.20211378
https://doi.org/10.1259/bjr.20211378
Autor:
Yohan Jun, Simon Arberet, Jean-Luc Starck, Dominik Nickel, Alireza Radmanesh, Yvonne W. Lui, Sunwoo Kim, Matthew J. Muckley, Mahmoud Mostapha, Jonas Teuwen, Zhengnan Huang, Nafissa Yakubova, Dosik Hwang, Geunu Jeong, Zaccharie Ramzi, Florian Knoll, Anuroop Sriram, Philippe Ciuciu, Chaoping Zhang, Bruno Riemenschneider, Hyungseob Shin, Jingyu Ko, Dimitrios Karkalousos
Publikováno v:
IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TMI.2021.3075856⟩
IEEE transactions on medical imaging
IEEE Transactions on Medical Imaging, In press, ⟨10.1109/TMI.2021.3075856⟩
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TMI.2021.3075856⟩
IEEE transactions on medical imaging
IEEE Transactions on Medical Imaging, In press, ⟨10.1109/TMI.2021.3075856⟩
Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reconstructing MR images with subsampled k-space data. We provided partici
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ada6cd85033aac2da6c4388d81c59f5a
https://hal.archives-ouvertes.fr/hal-03066150v2/document
https://hal.archives-ouvertes.fr/hal-03066150v2/document
Autor:
Enhao Gong, Greg Zaharchuk, Berkin Bilgic, Kawin Setsompop, Jongho Lee, Jaeyeon Yoon, Hosan Jung, Itthi Chatnuntawech, Jingyu Ko, Eung Yeop Kim, Jingu Lee, Woojin Jung, John M. Pauly
Deep neural networks have demonstrated promising potential for the field of medical image reconstruction. In this work, an MRI reconstruction algorithm, which is referred to as quantitative susceptibility mapping (QSM), has been developed using a dee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7513240f4686a7a272a7ebd0176e014a
Publikováno v:
Investigative Magnetic Resonance Imaging. 23:81
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a27c83f3d0812f14b0177c269e1ce2b8
https://doi.org/10.13104/imri.2019.23.2.81
https://doi.org/10.13104/imri.2019.23.2.81
Publikováno v:
Horticulture Research, Vol 5, Iss 1, Pp 1-9 (2018)
Fruit fungal infection: Effects on sugar metabolism A study by researchers in China provides insights into changes to sugar metabolism during fungal infection in post-harvest peaches. Fungal infections and associated disease development can alter sug
Externí odkaz:
https://doaj.org/article/08a220fc39ef431a9d5eab32df1d269a