Deformation equivariant cross-modality image synthesis with paired non-aligned training data

Joel Honkamaa, Umair Khan, Sonja Koivukoski, Mira Valkonen, Leena Latonen, Pekka Ruusuvuori, Pekka Marttinen

Abstract: Highlights•A generic cross-modality image synthesis architecture trainable with misaligned data.•The introduced deformation equivariance encouraging loss functions result in a robust and easily trainable method.•The method can be applied even to data sets with domain specific geometrical differences.•The method allows robust input conditioned adversarial training even with misaligned training data.