CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN

no code implementations • 7 Dec 2020 • Gyutaek Oh, Hyokyoung Bae, Hyun-Seo Ahn, Sung-Hong Park, Jong Chul Ye

In contrast to the conventional cycleGAN, our novel cycleGAN has only one generator and one discriminator thanks to the known dipole kernel.

Quantitative Susceptibility Map Reconstruction Using Annihilating Filter-based Low-Rank Hankel Matrix Approach

no code implementations • 25 Apr 2018 • Hyun-Seo Ahn, Sung-Hong Park, Jong Chul Ye

Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space.