Tissue segmentation can be performed using various techniques, broadly categorized into manual, semi-automated, and fully automated methods:
Manual Segmentation: Involves manually drawing boundaries around different tissue types using software tools. While accurate, it is time-consuming and subjective. Semi-Automated Segmentation: Combines manual input with automated algorithms to improve efficiency. For example, the user might provide initial seed points, and the software then propagates the segmentation boundaries. Automated Segmentation: Employs advanced algorithms such as deep learning and artificial intelligence to automatically delineate tissue components without human intervention. Techniques like convolutional neural networks (CNNs) are widely used in this context.
