Machine learning in imaging

Machine learning in imaging involves training computer algorithms to analyze and interpret visual data, such as photos or medical scans. By learning from many examples, these algorithms can recognize patterns, identify objects, or detect abnormalities without being explicitly programmed for every specific task. This process enables applications like medical diagnosis, facial recognition, or improving image quality, making the analysis faster and more accurate. Essentially, it allows computers to "learn" from data and improve their understanding of images over time, mimicking aspects of human visual perception.