This is a 12-week course designed to provide an understanding of fundamentals of Machine Learning (ML) for wide applications in Medical Imaging. Medical Imaging, which is an important specialty in medicine for diagnosis, prognosis, and intervention of different types of diseases including cancer, is increasingly moving toward quantitative approaches. ML algorithms are playing a key role in quantitative medical imaging analytics for disease diagnosis (detection) and prognosis (prediction). With the help of recent advances in ML and computer vision, novel predictive models are capable of diagnosing a disease with high accuracy and consistency, and predicting clinical outcomes (e.g., response to treatment) with an accuracy, which is beyond existing clinical methods.

The goal in this course is to help students develop the fundamental skills and expertise in Quantitative Medical Imaging and Machine Learning including Deep Learning with specific applications in Diagnostic and Prognostic Solutions for Medical Imaging. It is expected the students already be familiar with the basics of machine learning and the objective of this course is to cover the fundamentals of Medical Image Analysis including Computer-aided detection and diagnosis, and the applications of ML in Medical Image Analysis.