TY - GEN
T1 - Dual-domain cascaded regression for synthesizing 7T from 3T MRI
AU - Zhang, Yongqin
AU - Cheng, Jie Zhi
AU - Xiang, Lei
AU - Yap, Pew Thian
AU - Shen, Dinggang
N1 - Funding Information:
This work was supported by NIH grants (MH100217, MH108914, 1U01MH110274).
Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018
Y1 - 2018
N2 - Due to the high cost and low accessibility of 7T magnetic resonance imaging (MRI) scanners, we propose a novel dual-domain cascaded regression framework to synthesize 7T images from the routine 3T images. Our framework is composed of two parallel and interactive multi-stage regression streams, where one stream regresses on spatial domain and the other regresses on frequency domain. These two streams complement each other and enable the learning of complex mappings between 3T and 7T images. We evaluated the proposed framework on a set of 3T and 7T images by leave-one-out cross-validation. Experimental results demonstrate that the proposed framework generates realistic 7T images and achieves better results than state-of-the-art methods.
AB - Due to the high cost and low accessibility of 7T magnetic resonance imaging (MRI) scanners, we propose a novel dual-domain cascaded regression framework to synthesize 7T images from the routine 3T images. Our framework is composed of two parallel and interactive multi-stage regression streams, where one stream regresses on spatial domain and the other regresses on frequency domain. These two streams complement each other and enable the learning of complex mappings between 3T and 7T images. We evaluated the proposed framework on a set of 3T and 7T images by leave-one-out cross-validation. Experimental results demonstrate that the proposed framework generates realistic 7T images and achieves better results than state-of-the-art methods.
UR - http://www.scopus.com/inward/record.url?scp=85054084327&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00928-1_47
DO - 10.1007/978-3-030-00928-1_47
M3 - Conference contribution
AN - SCOPUS:85054084327
SN - 9783030009274
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 410
EP - 417
BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
A2 - Schnabel, Julia A.
A2 - Davatzikos, Christos
A2 - Alberola-López, Carlos
A2 - Fichtinger, Gabor
A2 - Frangi, Alejandro F.
PB - Springer Verlag
T2 - 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
Y2 - 16 September 2018 through 20 September 2018
ER -