“Artificial intelligence and medical image” is an auxiliary tool for the
computer to complete image classification, target detection, image segmentation, and
retrieval and assist doctors in diagnosing and treatment based on medical image
through deep learning. This chapter includes the review of Artificial intelligence (AI)
and its application in radiology, pathology, eye disease, deontology, dermatology, and
ophthalmology, which we have benefited from the use of AI methods. Modern
medicine is evidence-based medicine based on experiments. Doctors' diagnosis and
treatment conclusions must be based on corresponding diagnostic data. Imaging is an
important part of diagnosing, and 80% to 90% of data in the medical industry are
derived from medical imaging. Therefore, clinicians have a strong demand for images,
and they need to conduct a variety of quantitative analyses of medical images and
comparison of historical images to complete a diagnosis. In contrast to this qualitative
reasoning, AI is good at identifying complex patterns in the data and providing
quantitative assessments in an automated manner. Integrating AI into clinical
workflows as a tool to assist physicians allows for more accurate and repeatable
radiological assessments.
Keywords: Artificial intelligence, Deontology, Eye disease, Medical imaging,
Radiological assessments.
