Data-driven biomedical imaging and physics is an emerging interdisciplinary field that combines advanced medical physics concepts, deep learning algorithms, and biomedical imaging technologies to develop new approaches for diagnosis, treatment, and research in the biomedical field. The main goal of this course is to provide background knowledge of biomedical imaging and physics, introduce the fundamentals of deep learning and data-driven techniques, describe the problems and data-driven solutions in imaging and medical physics, and present clinical use cases and successful examples in data-driven biomedical physics. It is anticipated that the students will gain useful knowledge and practical skills to advance the field of data-driven biomedical imaging and physics in the near future. Prerequisite: Basic knowledge on AI & deep learning.
1 units · Medical Satisfactory/No Credit
Data-driven biomedical imaging and physics is an emerging interdisciplinary field that combines advanced medical physics concepts, deep learning algorithms, and biomedical imaging technologies to develop new approaches for diagnosis, treatment, and research in the biomedical field. The main goal of this course is to provide background knowledge of biomedical imaging and physics, introduce the fundamentals of deep learning and data-driven techniques, describe the problems and data-driven solutions in imaging and medical physics, and present clinical use cases and successful examples in data-driven biomedical physics. It is anticipated that the students will gain useful knowledge and practical skills to advance the field of data-driven biomedical imaging and physics in the near future. Prerequisite: Basic knowledge on AI & deep learning.
Offered in Spring 2027 at Stanford University.