Advanced Image Processing and Analysis

Combined Undergraduate/Graduate course, Western University, ECE 4438b/ ECE 9022b/ECE 9202b/BioMed 9519b/BioPhys 9519b/CAMI 9519b, 2019

Digital image processing has various applications ranging from remote sensing and entertainment to medical applications. This course explores a few major areas of digital image processing at an advanced level, with primary emphasis on medical applications. Topics covered included image segmentation, image registration, validation of image processing algorithms, and image processing using the Insight Toolkit (ITK) and Jupyter Notebook. Examples will be presented to give the students exposure to real world applications.

Lectures

  • Monday 2:30-3:20pm, SH-3307
  • Tuesady 5:30-7:20pm, SEB-3109
  • Start Date: Monday, January 7, 2019

Site Usage

The method of course material delivery will be based on Jupyter Notebook which is a web-based and interactive front-end to the programming language python. The open-source image processing library, Insight Segmentation and Registration Toolkit (ITK), will be heavily utilized. Akin to the popular Matlab environment, this is a totally interactive with nothing to compile.

When needed, “skeleton” PowerPoint slides and Jupyter Notebook will be used to present course materials. These skeleton slides/Notebooks are not complete, and I will fill them in during the class to demonstrate the course materials in a logical and paced manner. These course materials will be posted on OWL website ahead of the class so you can print them and fill them in during the class: these skeleton slides will be posted on the left panel under “Lectures”. As I continuously fill in these skeleton slides during each class, they will be re-posed under “Lectures” at the end of each class.

Please note the other course materials posted on OWL:

  • course outline,
  • assignment time tables - lists distribution and due dates for assignments,
  • assignments - will hold assignments and solutions.

Expectations

Here is what I expect of every students:

  • Honesty: some assignments and projects (for graduate students) will be performed in groups, but each group should do its own work,
  • Attend all classes: I’d like to know you and you should know me. As there is no textbook for this course, it is a good idea for you to attend the class,
  • Participation: this course is designed to be interactive. It is a good idea for your to ask questions in class and share ideas,
  • Be timely: submit all assignments on time. This is always a good practice and failure to do so will result in heavy penalty,
  • Keep up: course materials are built upon progressively. Review lectures and do your homework in a timely manner. Read emails from me as it is the best way for me to communicate with you outside of class,
  • No MISSING midterm/assignments/final examination: unless you have proper and documented reasons, missing assignments/midterms/final examination will result in a score of zero, with NO EXCEPTION.

What you can expect of me:

  • Effort: this course is designed from the group up: as technologies are changing so shall the way we teach. I put a lot of efforts in developing the course materials. My aim is to motivate you, get you ready for your future career and more importantly, teach you a skill that will help you in the long run,
  • Punctually: I am never late for class and will always arrive early unless something goes wrong that is beyond my control,
  • Availability: I respect posted office hours. I also try to be flexible to accommodate your schedule. I cannot always be available since I have other duties and deadlines, but I’ll try my best,
  • Fairness: I never take off marks unless justified.