Computer Aided Diagnosis typically involves several steps:
1. Image Acquisition: High-resolution images of tissue sections are acquired using a microscope or a digital scanner. 2. Preprocessing: This step includes enhancing the image quality, removing noise, and normalizing the data. 3. Segmentation: The image is divided into regions of interest, such as differentiating between different types of tissues or identifying cellular structures. 4. Feature Extraction: Key features such as shape, texture, color, and pattern are extracted from the segmented regions. 5. Classification: Machine learning algorithms are used to classify the extracted features into different categories, such as benign or malignant tissues. 6. Decision Support: The results are then presented to the pathologist, aiding in the final diagnosis.
