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

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