High-precision semantic segmentation of apple internal diseases based on CT imaging and deep learning

• Designed a CT image framework for detecting moldy core and browning in apples. • Built a multi-category annotated dataset with an ROI slice extraction strategy. • Applied generative data augmentation methods to enhance data diversity and quality. • Enhanced TransUNet with CSWin Transformer and attention to boost segmentation.