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Tensorflow implementation of our unsupervised cross-modality domain adaptation framework. This is the version of our TMI paper. Please refer to the branch SIFA-v1 for the version of our AAAI paper. Raw data needs to be written into tfrecord format to be decoded by ./data_loader.py. The pre-processed data has been released from our work PnP-AdaNet.

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In this paper, we present a new recipe of inter-frame attention block, namely Stand-alone Inter-Frame Attention (SIFA), that novelly delves into the deformation across frames to estimate local self-attention on each spatial location.

a pytorch version for SIFA, Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

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