Abstract
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.
Original language | English |
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Title of host publication | Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings |
Editors | Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger, Alejandro F. Frangi |
Publisher | Springer Verlag |
Pages | 410-417 |
Number of pages | 8 |
ISBN (Print) | 9783030009274 |
DOIs | |
Publication status | Published - 2018 |
Event | 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain Duration: 2018 Sept 16 → 2018 Sept 20 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11070 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 |
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Country/Territory | Spain |
City | Granada |
Period | 18/9/16 → 18/9/20 |
Bibliographical note
Publisher Copyright:© Springer Nature Switzerland AG 2018.
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science