Semantic segmentation image annotation is used to annotate various types of medical images like X-rays, MRI and CT scans of several organs or parts of the human body. It also helps to annotate or highlight the human body organs partially that are injured due to illnesses.
The key benefit of semantic segmentation is, it helps in the classification of objects with the help of computer vision using three processes namely first classification, second object detection and last image segmentation. These processes largely help machines to classify the affected area of the body organs.
This highly accurate image annotation method can be used for annotating the X-ray of the whole body including the brain, liver, prostate and kidney for the exact treatment of several diseases. The annotation technique in these body parts works to segment mainly the affected parts to make it identifiable to machine learning algorithms.
To understand the actual insight of the clinical images to foresee similar illnesses when implied in real-life formed as an AI model, semantic segmentation comes in the best use. It offers the ideal medical imaging datasets for machine learning or deep learning AI models in medical care.