ELEC 444/6661 Medical Image Processing
Department of Electrical and Computer Engineering
Concordia University

Instructor: Hassan Rivaz
Course description: This course covers the principles and algorithms used in the processing and analysis of medical images. Topics include denoising, machine learning, image registration and similarity metrics. Image analysis methods on the most common medical imaging modalities (X-ray, MRI, CT, ultrasound) will be covered. Projects and assignments will provide students experience working with actual medical imaging data.
Credits: Undergraduate course ELEC 444: 3 credits. Graduate course ELEC 6661: 4 credits. The graduate course requires carrying out a significantly more demanding project, which accounts for the exra credit.
Location & time: FG B055 SGW, Tuesdays 5:45PM to 8:15PM
Text Book: Medical Image Processing, 2014, By Wolfgang Birkfellner, CRC Press, ISBN: 978-1466555570.
Reference Book: Medical Image Processing, 2009, By Geoff Dougherty, Cambridge University Press, ISBN: 9780521860857.
Assignments: Three assignments + one final project (in MATAB or another language based on student preference). Marker: Ms. Fatemeh Mohamadi. Email: fmohammadi92 ATsign gmail.com
POD: Ms. Zara Vajihi. Email: zvajihi73 ATsign gmail.com
Lab time & location: Thursdays, 1:30PM to 5:30PM, loc: H903. Ask questions from POD Ms. Zara Vajihi. It is not mandatory to attend lab. No material is presented here, only questions are answered.
Undergraduate (3 credits)Graduate (4 credits)
Midterm exam2020
Final exam5030

AssignmentsPost dateDue date Points
Assignment 1Wednesday Sept 20, 9AMFriday Sept 29, 9AM 1 point
Assignment 2Wednesday Oct 11, 9AMFriday Oct 20, 9AM4.5 points
Assignment 3Wednesday Oct 25, 9AMFriday Nov 3, 9AM4.5 points

Week Topic
1, Sep 5 Logistics, introduction to X-ray, CT and nuclear imaging
2, Sep 12 (Guest Lecture by Dr. Grova) Electroencephalography (EEG), Magnetoencephalography (MEG), inverse problem
3, Sep 19 Introduction to ultrasound and Magnetic Resonance (MR) imaging, images in Matlab
4, Sep 26 (first half by Dr. Xiao) More on MR, convolution, aliasing in medical images
5, Oct 3 Denoising techniques in medical imaging, edge detection in medical images
6, Oct 10 Machine learning in medical imaging
Oct 17 Midterm in class (mark your calendar)
8, Oct 24 Introduction to image registration, similarity metrics (sum of squared differences, normalized cross correlation), Correlation ratio, joint entropy
9, Oct 31 Continuing similarity metrics (Mutual Information, MI). Case study 1: Computer vision and motion estimation in ultrasound elastography
10, Nov 7 Case study 1: Computer vision and motion estimation in ultrasound elastography
11, Nov 14 Case study 2: Registration (fusion) of medical images
12, Nov 21 Review
13, Nov 28 Student presentations

Undergraduate students: ELEC 364 or ELEC 342 Signals and Systems or instructor's permission. Graduate students: none.

Database of images possibly useful for projects:

1) BrainWeb MRI link ,
2) Ultrasound RF data link ,
3) 3D MRI and ultrasound link ,
4) More 3D MRI and ultrasound link ,
5) Microscopy link
6) CT link