Improved 3D U-Net model-based preschool child lung image region-of-interest segmentation method

The invention provides a preschool child lung image region-of-interest segmentation method based on an improved 3D U-Net model. The preschool child lung image region-of-interest segmentation method comprises the following steps: (1) collecting CT image data of a preschool child patient for preprocessing; (2) dividing the preprocessed image into a training set, a verification set and a test set; (3) a segmentation model is constructed, the segmentation model adopts an improved 3D U-Net network model, a channelized Transform module is designed between an encoder and a decoder of the 3D U-Net network model, and a UCTransNet framework is constructed to replace jump connection in U-Net so as to better fuse characteristics of the encoder; (4) sending the preprocessed training set into the constructed segmentation model for training; and (5) inputting a to-be-segmented lung image of the preschool child into the trained segmentation model to obtain a region of interest of the lung image. According to the method, the