ICMSC: Intra- and Cross-modality Semantic Consistency for Unsupervised Domain Adaptation on Hip Joint Bone Segmentation

23 Dec 2020 • Guodong Zeng • Till D. Lerch • Florian Schmaranzer • Guoyan Zheng • Juergen Burger • Kate Gerber • Moritz Tannast • Klaus Siebenrock • Nicolas Gerber

Unsupervised domain adaptation (UDA) for cross-modality medical image segmentation has shown great progress by domain-invariant feature learning or image appearance translation. Adapted feature learning usually cannot detect domain shifts at the pixel level and is not able to achieve good results in dense semantic segmentation tasks... (read more)

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

METHOD

TYPE

Batch Normalization