CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN

7 Dec 2020 • Gyutaek Oh • Hyokyoung Bae • Hyun-Seo Ahn • Sung-Hong Park • Jong Chul Ye

Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging (MRI) technique which provides spatial distribution of magnetic susceptibility values of tissues. QSMs can be obtained by deconvolving the dipole kernel from phase images, but the spectral nulls in the dipole kernel make the inversion ill-posed... (read more)

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METHOD	TYPE
Residual Connection	Skip Connections
Batch Normalization	Normalization
Residual Block	Skip Connection Blocks
Convolution	Convolutions
PatchGAN	Discriminators
Sigmoid Activation	Activation Functions
Tanh Activation	Activation Functions
Leaky ReLU	Activation Functions
Cycle Consistency Loss	Loss Functions
ReLU	Activation Functions
GAN Least Squares Loss	Loss Functions
Instance Normalization	Normalization
CycleGAN	Generative Models

METHOD

TYPE

Residual Connection