Automated segmentation typically involves several steps. Initially, the medical image is preprocessed to enhance its quality and remove any noise. This is followed by the application of segmentation algorithms, which can be based on techniques such as thresholding, region growing, clustering, or deep learning. The segmented output is then post-processed to refine the boundaries and ensure the accuracy of the segmentation.
