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Quantitative Susceptibility Mapping (QSM) is a new phase-based technique forquantifying magnetic susceptibility. The existing QSM reconstruction methodsgenerally require complicated pre-processing on high-quality phase data. Inthis work, we propose to explore a new value of the high-pass filtered phasedata generated in susceptibility weighted imaging (SWI), and develop anend-to-end Cross-connected $\Psi$-Net (C$\Psi$-Net) to reconstruct QSM directlyfrom these phase data in SWI without additional pre-processing. C$\Psi$-Netadds an intermediate branch in the classical U-Net to form a $\Psi$-likestructure. The specially designed dilated interaction block is embedded in eachlevel of this branch to enlarge the receptive fields for capturing moresusceptibility information from a wider spatial range of phase images.Moreover, the crossed connections are utilized between branches to implement amulti-resolution feature fusion scheme, which helps C$\Psi$-Net capture richcontextual information for accurate reconstruction. The experimental results ona human dataset show that C$\Psi$-Net achieves superior performance in our taskover other QSM reconstruction algorithms.

Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected $\Psi$-Net