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This invention provides a method for constructing a small bowel CT image recognition and segmentation network model and a recognition method. The construction method includes the following steps: acquiring several small bowel CT images showing lesions and constructing an image dataset, dividing the dataset into a training set and a test set proportionally; enhancing the image dataset in the above steps using dynamic stochastic resonance enhancement; constructing a U-Net network model and training the network model using the enhanced training set obtained in the above steps; testing the network model using the enhanced test set obtained in the above steps, and completing the model construction. This invention proposes a method for enhancing CT images based on dynamic stochastic resonance, which can effectively enhance useful signals in the original image. Since medical image processing is mainly used to assist doctors in diagnosis, the input is an image, and the output is also an image that is easier for doctors to use. This invention establishes a U-shaped neural network that meets this requirement.