The process typically involves several steps: 1. Image Acquisition: Tissue samples are stained and scanned using high-resolution imaging systems to create digital slides. 2. Preprocessing: Images are preprocessed to enhance quality and remove any artifacts. This may include noise reduction, contrast enhancement, and normalization. 3. Segmentation: The tissue components are segmented, meaning they are separated into distinct regions (e.g., identifying individual cells or tissue structures). 4. Feature Extraction: Various features, such as shape, size, and intensity, are extracted from the segmented components. 5. Classification and Quantification: Machine learning algorithms classify the components based on predefined criteria and quantify them accordingly.
