Computational Methods for Biomedical Image Analysis and Interpretation
Description
Biomedical imaging is an explosive field, as the technologies for visualizing the body become increasingly powerful. Imaging is at the core of medical practice, as nearly all patients have some sort of imaging done during care. Imaging informatics is the science of analytic, storage, retrieval and interpretive methods to optimally use imaging data in biomedicine. This field spans a broad spectrum of topics that includes engineering, computer science, statistics, radiology and medicine.
This course will provide a broad overview of this field as well as explore the foundational techniques required to process, analyze and use images for scientific discovery and applications. Case studies include linking image data to genomic, phenotypic and clinical data, developing representations of image phenotypes and research applications. Students will participate in a project. Enrollment for 3 units with reduced project requirements requires instructor consent.
Prerequisites
Programming ability at the level of CS106A, familiarity with statistics, basic biology and familiarity/experience with Python programming.
Topics include
- Types of imaging methods and how they are used in biomedicine
- Image processing, enhancement and visualization
- Computer-assisted detection, diagnosis and decision support
- Access and utility of publicly available image data sources
- Computer reasoning with images
- New questions and case studies in biomedicine using imaging informatics
Course Availability
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.
