Biomedical Informatics 260: Computational Methods for Biomedical Image Analysis and Interpretation (BIOMEDIN 260, RAD 260)
Biomedical imaging is an exploding field. The
technologies for visualizing the body (the imaging modalities) are
becoming very powerful, providing exquisite images of tissue morphology,
revealing tissue function, and even beginning to see molecular events
such as gene expression. Imaging is at the core of medical practice;
nearly all patients have imaging of some sort during care, and many
studies produce thousands of images. Just as the genetic data explosion
has fueled the field of bioinformatics, the growth in digital imaging is
necessitating techniques in imaging informatics.
Imaging Informatics is the science of analytic, storage, retrieval, and interpretive methods to optimally use the increasingly voluminous imaging data in biomedicine, and integrate and understand them in the context of complementary molecular and clinical information to improve clinical diagnosis and therapy in medicine. Imaging informatics spans a broad spectrum of topics that include engineering, computer science, statistics, radiology, and medicine. This course will provide a broad overview this field as well as the foundation techniques required to process, analyze, and use images for scientific discovery and applications.
Topics covered in this course:
- 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
- Linking imaging data to clinical data and phenotypes
- Computer reasoning with images
- New questions in biomedicine using imaging informatics. Case studies.
Also known as: RAD 260
Units: 4 (or 3 with consent of instructor)
Lectures: Spring Quarter 2017-2018, Monday and Wednesday 1:30 PM - 2:50 PM, Huang Engineering Center, Room 18
TA-led Section: MSOB X-393 (3rd floor)
First class: Monday, April 2, 2018
Prerequisites: Programming ability at the level of CS 106A, familiarity with statistics, basic biology, knowledge of Python (highly recommended), or approval of the instructor.
Grading: Assignments (45% total), Participation (10%), Midterm (15%), Final Project (30%)
Participation: There are many different ways to participate, including but not limited to attending class, attending section, asking questions, and contributing to discussions on Piazza.
Ningrui Li (ningruil [at] stanford.edu)
Contact/Questions: Most questions should be posted to Piazza Discussions page, so that all students can benefit from the answers. Other queries can either be emailed privately to TAs or Professors.
This course is designed for:
• Medical students
• Medical, pediatric, surgical or other fellows with an interest in learning and using imaging informatics in research
• Interested undergraduates
• Auditors welcome including medical staff, medical/pediatric/surgical fellows, post-doctoral fellows, and undergraduates. Please contact us to be added to the class email list.
Required books: None (the course will be taught using recent publications)
• Digital Image Processing in Matlab - Gonzales and Woods. Also see here.
• Insight into Images - Yoo
• Digital Image Communications in Medicine - Pianykh
• Practical Imaging Informatics - Branstetter
• Naked to the Bone - Bettyann Kevles
Software and computing resources
Final Project Presentations
Students with Documented Disabilities