Summer 2021 - CMPT 340 D100

Biomedical Computing (3)

Class Number: 3049

Delivery Method: In Person


  • Course Times + Location:

    Tu 2:30 PM – 4:20 PM

    Fr 2:30 PM – 3:20 PM

  • Prerequisites:

    Completion of 60 units including one of CMPT 125, 126, 128, 135, with a minimum grade of C- or CMPT 102 with a grade of B or higher.



The principles involved in using computers for data acquisition, real-time processing, pattern recognition and experimental control in biology and medicine will be developed. The use of large data bases and simulation will be explored.


Biomedical computing is a rapidly emerging area that is revolutionizing medicine and biology. It focuses on the use of computational and mathematical techniques to accelerate scientific discovery and to improve diagnosis, treatment, and understanding of diseases. The general objectives of the course are: To give the student breadth in the topics related to the use of computers in biology, medicine, and healthcare, in both theory and application. To enable the student to converse knowledgeably with radiologists, physicians, and MDs about these topics and related technologies. To learn the technical basis of many aspects of the use of technology in biomedicine (e.g. data acquisition, biosignal/image processing and visualization, feature representation and extraction, data interpretation and machine learning), current and future trends, and their benefits and limitations.



  • Biosignals and signal analysis: The properties of different types of biosignals (e.g. EEG and ECG) and the techniques used for processing and analysis of biosignals (e.g. frequency domain filtering).
  • Medical imaging and image processing: The acquisition of different medical images (e.g. magnetic resonance imaging and X-ray computed tomography) and the techniques used for processing, analysis, and visualization of medical images (e.g. image segmentation and registration).
  • Medical knowledge and decision support: The representation of medical knowledge and the computational methods used to assist in decision-making (e.g. Boolean and fuzzy logic, artificial neural networks, and decision trees, flowcharts, and tables).
  • Biostatistics: Statistical reasoning methods in medicine (e.g. hypothesis testing, multivariate analysis).
  • Databases in Medicine: Computer-based patient records and the standards for storage, retrieval, and electronic communication of medical data (e.g. DICOM, PACS, SNOMED)
  • Case studies, recent advancements, future trends: These may include: Computers-assisted and robotic surgery, computer-aided diagnosis, tele-medicine, biometrics, radiotherapy, human modelling, security in medical information systems, micro-array data analysis, computers for drug design, and more.



Grading to be announced during the first week of classes.



Reference Books

  • Clinical Decision Support Systems: Theory and Practice, E. S. Berner, Springer, 2010, 9781441922236, 2nd Edition
  • Information Technology for the Health Professions, L. Burke and B. Weill, Pearson Prentice Hall, 9780132897648, 4th Edition
  • PACS and Imaging Informatics: Basic Principles and Applications, H. K. Huang, Wiley, 2004, 9780471251231
  • Neural Networks and Artificial Intelligence for Biomedical Engineering, D. L. Hudson, M. E. Cohen, Wiley, 1999, 9780780334045
  • Handbook of Medical Informatics 1st Edition, J. Bemmel, M. Musen, Springer Verlag, 1997, 9783540633518, Copies available via amazon. There is a hard copy version available to be signed out on the SFU library

Registrar Notes:


SFU’s Academic Integrity web site is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University.


Teaching at SFU in summer 2021 will be conducted primarily through remote methods, but we will continue to have in-person experiential activities for a selection of courses.  Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning ( or 778-782-3112).