CS 736 – ALGORITHMS FOR MEDICAL IMAGE PROCESSING
Course offered in:
Spring 2017
Instructors:
Suyash Awate
Motivation:
The course deals with basic algorithms used in medical image processing. This is a really good course for those interested in hard core mathematics and optimization algorithms in action.
Course Content:
The topics covered in this course are as follows –
- Introduction to Mathematical imaging models, Noise models
- Computed Tomography (CT), Magnetic resonance imaging (MRI) (including diffusion MRI, functional MRI)
- Image reconstruction Methods
- Image denoising Methods
- Image segmentation Methods
- Anatomical shape analysis Methods
- Image registration Methods
Feedback on Lectures:
The instructor taught with the help of slides, occasionally using the board to derive or explain an algorithm. Paying attention in class is highly advised since it makes preparation for exams easier. The instructor readily solved the doubts and was jovial while teaching. Classes were held in evening slots, 2 days a week for 1.5 hours each.
Feedback on Tutorials, Assignments and Exams:
There were a total of 5 assignments given based on the implementation of the material taught in class. Assignments demanded considerable amount of time but they also helped in understanding of the material taught in class which made exams seem easy.
There was an end semester exam, a mid semester exam and a quiz. The exams were closed book (cheat sheets allowed as per the instructor’s will), based on the material covered in the class. They were moderate in difficulty level, and mostly based on the material discussed in class. Easy to score if basic concepts of each topic is understood, not much rote learning required.
Weightage and Grading:
Assignments – 35% Exams – 50% (individual weightages not known) Course Project – 15%
Study Material and References:
The content uploaded on the moodle was more than enough.
Review by – Parth Kothari (parthkothari811@gmail.com)
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