Deep learning models, particularly convolutional neural networks (CNNs), have shown remarkable success in tissue segmentation tasks. These models can automatically learn complex patterns and features from large datasets, improving segmentation accuracy. By leveraging large-scale annotated datasets, CNNs can generalize better across different imaging modalities and patient populations, making them highly effective in clinical settings.
