CINENet: Deep Learning-based 3D Cardiac CINE MRI Reconstruction with Multi-coil Complex-valued 4D Spatio-Temporal Convolutions

Thomas Kustner; Niccolo Fuin; Kerstin Hammernik; Aurelien Bustin; Haikun Qi; Reza Hajhosseiny; Pier-Giorgio Masci; Radhouene Neji; Daniel Rueckert; Rene Botnar; Claudia Prieto Vasquez

CINENet: Deep Learning-based 3D Cardiac CINE MRI Reconstruction with Multi-coil Complex-valued 4D Spatio-Temporal Convolutions

Imperial College London

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	Nature Scientific Reports
Publication status	Accepted/In press - 31 Jul 2020

Cite this

@article{2b8eadb292c24e9eb88c56864ecb073e,

title = "CINENet: Deep Learning-based 3D Cardiac CINE MRI Reconstruction with Multi-coil Complex-valued 4D Spatio-Temporal Convolutions",

author = "Thomas Kustner and Niccolo Fuin and Kerstin Hammernik and Aurelien Bustin and Haikun Qi and Reza Hajhosseiny and Pier-Giorgio Masci and Radhouene Neji and Daniel Rueckert and Rene Botnar and \{Prieto Vasquez\}, Claudia",

year = "2020",

month = jul,

day = "31",

language = "English",

journal = "Nature Scientific Reports",

}

TY - JOUR

T1 - CINENet: Deep Learning-based 3D Cardiac CINE MRI Reconstruction with Multi-coil Complex-valued 4D Spatio-Temporal Convolutions

AU - Kustner, Thomas

AU - Fuin, Niccolo

AU - Hammernik, Kerstin

AU - Bustin, Aurelien

AU - Qi, Haikun

AU - Hajhosseiny, Reza

AU - Masci, Pier-Giorgio

AU - Neji, Radhouene

AU - Rueckert, Daniel

AU - Botnar, Rene

AU - Prieto Vasquez, Claudia

PY - 2020/7/31

Y1 - 2020/7/31

M3 - Article

JO - Nature Scientific Reports

JF - Nature Scientific Reports

ER -