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Rethinking Dual-Domain Undersampled MRI reconstruction: domain-specific design from the perspective of the receptive field
- Publication Year :
- 2023
-
Abstract
- Undersampled MRI reconstruction is crucial for accelerating clinical scanning. Dual-domain reconstruction network is performant among SoTA deep learning methods. In this paper, we rethink dual-domain model design from the perspective of the receptive field, which is needed for image recovery and K-space interpolation problems. Further, we introduce domain-specific modules for dual-domain reconstruction, namely k-space global initialization and image-domain parallel local detail enhancement. We evaluate our modules by translating a SoTA method DuDoRNet under different conventions of MRI reconstruction including image-domain, dual-domain, and reference-guided reconstruction on the public IXI dataset. Our model DuDoRNet+ achieves significant improvements over competing deep learning methods.<br />Comment: 2024 IEEE International Symposium on Biomedical Imaging (ISBI)
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2303.10611
- Document Type :
- Working Paper