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Biomedical Informatics 260: Computational Methods for Biomedical Image Analysis and Interpretation (BIOMEDIN 260, RAD 260)

General Course Information

|Overview | Detail | Staff | Video Lectures | Audience | Textbooks


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 2016-2017, Monday and Wednesday 1:30 PM - 2:50 PM, Location Gates B03
Map to Gates

TA-led Section: Fridays 1:30-2:50 PM, Location: Littlefield 341

First class: Monday, April 3, 2017

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: BMI260 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 Piazza Discussions.



Part I: David Paik, PhD, Adjunct Lecturer, Radiology

Part II: Daniel Rubin, MD, MS, Associate Professor Profile

Teaching Assistants:

Darvin Yi (
Albee Ling (

Office Hours:

Bring questions to Friday section meeting.
Location: Littlefield 341

Professor Rubin: by appointment (email Kelly Englese to set up a meeting time). Lucas P285.

Professor Paik: by appointment (email Professor Paik directly, then email Professor Paik first, then Maggie Bos ( to set up a meeting time). Lucas P287.

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:

• Graduate students in biomedical informatics, computer science, bioengineering, or other related disciplines
• 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.


The video lectures can be accessed via SCPD.
All handouts are released on Canvas.


Required books: None (the course will be taught using recent publications)

Recommended books:

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

Useful datasets:

Image Datasets



Students are encouraged to post questions on Piazza.


Readings are linked from each lecture on the Syllabus page. Expect two to three readings per class as preparation.

Software and computing resources: please install python notebook on your computer

Collaboration policy:

You can talk with others in the class about the class projects, but you must turn in your own individual work and do the programming yourself.

Due dates:

Assignments are due at or before 11:59 PM on Fridays, and new assignments released on Friday morning. No late days are allowed. Please contact the TAs for special accommodation if applicable.

Course projects

During the quarter, the students will undertake developing and implementing four substantial imaging informatics applications, increasing in difficulty during the quarter.

Midterm Exam

Based on the lectures and the readings. Open book. To be held during class, Monday, May 15th.

Final Project Presentations

To be held in MSOB X275 on Monday, June 12 from 3:30 PM - 6:30 PM.

Honor code

Stanford University's Honor Code will be observed and uphold at all times.

Students with Documented Disabilities

Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone: 723-1066, URL: