There are several techniques of image annotation used to establish the AI model through machine learning. Some of them include cuboid annotation, polygon annotation and bounding box. However, semantic segmentation is the best demonstrative technique that provides the detailed findings with illnesses segmented and categorised in an individual class.
Medical image segmentation aids to detect the pixels of lesions or organs from the medical images in the background like MRI images or CT, which is the most complex task when it comes to medical image analysis. However, it offers crucial details on the volumes and shapes of distinct organs detected in the radiology section. Semantic segmentation is primarily used for the images that fit into a single class to make them identifiable.