Automatic segmentation employs advanced techniques such as deep learning, particularly convolutional neural networks (CNNs), which are trained on large datasets of annotated images. These networks learn to recognize patterns and features specific to cancerous tissues. The process typically involves pre-processing the images, feeding them into the trained model, and post-processing the output to refine the segmentation. The result is a segmented image where different tissues, including tumors, are identified and highlighted.
