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The document presents the I2 U-Net, a novel dual-path U-Net designed for medical image segmentation, which enhances the utilization of historical information through rich interactions between its two paths. This architecture incorporates a multi-functional information interaction module and a holistic information fusion and augmentation module, allowing for improved feature learning and segmentation performance on various medical imaging tasks. Extensive experiments demonstrate that I2 U-Net outperforms exi

Author

vvv tr

Language

EN