Global context and boundary structure-guided network for cross-modal organ segmentation

•We firstly propose to utilize global context to guide deformable convolution, which can obtain reasonable receptive fields with a global perspective.•We introduce the class-wise global context to handle intensity non-uniformities in cross-modal organ segmentation.•A novel loss which focuses on the areas near the boundary is proposed here and can deal with the border blurs well.