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This invention discloses a method for segmenting colorectal cancer polyps based on cross-domain feature fusion. It relates to the field of medical image segmentation technology. The method includes: acquiring an image dataset with diverse polyp morphologies; constructing an FFNet network model, comprising: a pyramid visual encoder, a multi-scale feature enhancement module, an adaptive filtering module, and a similarity aggregation module connected sequentially; and fusing image domain and frequency domain features from the image dataset using the FFNet network model to achieve polyp segmentation. This invention achieves more accurate and comprehensive segmentation through the FFNet network model.