Medical imaging informatics is a rapidly growing field that combines the principles of medical imaging and informatics to improve the acquisition, management, and interpretation of medical images. This chapter introduces the basic concepts of medical imaging informatics, including image processing, feature engineering, and machine learning. It also discusses the recent advancements in computer vision and deep learning technologies and how they are used to develop new quantitative image markers and prediction models for disease detection, diagnosis, and prognosis prediction. By covering the basic knowledge of medical imaging informatics, this chapter provides a foundation for understanding the role of informatics in medicine and its potential impact on patient care.

Medical Imaging Informatics and Artificial Intelligence at UCSF is headed by Dr. Dugyu Tosun-Torgut and brings together world-class researchers from multiple disciplines in order to find new, innovative ways to use artificial intelligence and imaging for medical diagnosis. By uniting neurologists, engineers, and data scientists Medical Imaging Informatics and Artificial Intelligence will be extremely impactful in increasing the scope of our current imaging systems when it comes to the brain. The Medical Imaging Informatics and Artificial Intelligence Lab at UCSF aims to foster a truly collaborative environment. All team members are expected to contribute and participate in meaningful ways as we seek to discover novel new ways to utilize technology to better diagnose and treat patients. We value long term partnerships and create a trusting environment for all to succeed.