With the rise in advancements in computer vision-based ML models, AI has become highly prevalent today. When there is more utility of training data with the ML algorithm, there will be more options that simplify the process of predicting the results accurately in several cases for the healthcare industry.
The annotated medical images are put to good use to detect the ailments in the body through machines. This helps in making the training data more productive and useful. Medical image annotation is used to form such data with a high level of precision. Medical image annotation involves the process to label the imaging data such as CT scan, MRI and Ultrasound for ML training. This process plays a crucial role in the telemedicine sector.
Image Annotation & Its Role in AI Health Sector
Image annotation helps to identify different types of illnesses with the help of AI-driven machines, computer systems and devices. The process offers the data to the learning algorithms and hence the model plays the role of a user to check for such illnesses when there are similar images placed on the system. Whether it is a minor bone fracture or a life-threatening disease such as cancer, image annotation helps in detecting maladies with accuracy.