CMPT 419: Biomedical Image Computing -- Special Topics in AI
Cross listed with
CMPT 829: Biomedical Image Computing -- Special Topics in Bioinformatics
Next offering: Fall 2013.
Note to non-SFU graduate
For non-SFU undergraduate students, inquire about attending CMPT419 by emailing
- learn about biomedical image file format (including DICOM, Analyze,
MINC), and how they are different from images you capture with your
Example information related to a DICOM medical image file.
- learn about different approaches for processing, and
enhancing (reducing noise) in medical images (including spatial,
frequency-domain, and morphological filtering).
Enhancing an MRI image of a mouse kidney.
Reducing noise in a heart image.
- learn how to model variability in anatomical shapes and
how can this translate into improved healthcare. You can calculate the mean
and variance of some numbers, but how do you find the "mean and variance" of
(left) ventricle of the heart in an ultrasound image. (middle) Some acceptable
and implausible ventricular shapes. (right) average ventricle shape and
- learn what biomedical image segmentation is, different approaches
(including clustering, deformable models, region-based and level-set
approaches), and why is it important for medicine.
A PDE-based optimization method is used to move the red contour in a brain image
and identify the corpus callosum (bridge connecting left and right brain
Schematic diagram of a graph-theoretic approach for
identifying objects in a medical image.
tools for 3D and more complicated images.
- understand what medical biomedical image registration is, its
applications in health care, and what its basic building blocks.
Before (top) and after (bottom) registration of radioactivity (orange)
to anatomy from CT image (gray).
Registering an extended knee to a flexed knee.
- learn how to use 3D and medical imaging software to view and process
your data. Think of these as Photoshop-
Example software screenshots and applications.
- Project: The course involves working on a biomedical image
computing project. A wide range of projects related to the above topics is
possible. The project topic can be either initiated by the student or
recommended by the instructor. The project may be very clinical
application oriented or may deal with a theoretical aspect of
computational/mathematical techniques for medical image analysis, or a
combination of both (see some example
projects at our Medical Image
- Advantages: there are many other advantages to studying topics at
the interface between computing and medicine, including: wider
career opportunities, graduate studies and
funding, working with state-of-the-art software and hardware, collaborating
with doctors and accessing valuable medical data... more are mentioned
- More details about the course are available in the
formal course outline
(left) vasculature in 3D brain MR angiography (head seen from above, nose in
lower right corner) (right) spinal cord detection in MRI
rotator cuff muscle in the shoulder