Yasser Mostafa Kadah

Professor of Biomedical Engineering

EE 684 - Computer Applications in Medicine

Spring 2016 - Spring 2017 - Fall 2018

 

Class Approach

This course uses an applied, research problem-based approach to learning. That is, instead of the conventional lectures and exams, the course will consider a number of real research problems and learn the necessary tools in the context of solving each of these research problems. This approach has the following advantages:
  • The research problems considered can be easily extended to thesis topics.
  • The tools considered have general utility and can be extended for use in other research problems
  • The research problem-centered setting is similar to what the graduate student will be doing in his thesis. Therefore, the techniques used to address the research problems can also prepare the student before starting the thesis work.

The learning process will be as follows:

  • Instructor explains the research problem and breaks it into its basic engineering problem components
  • Instructor shows students example ways to solve each of these engineering problems with practical demonstrations
  • Instructor shows students how to assess the resultant solution of the problem on both simulated and real data sets to verify the performance
  • Instructor assigns each student to study a slightly modified version of the method considered and report on it in the form of a paper.
  •  Student can use the instructor as a resource to ask for help when facing difficulties getting started
  • Instructor encourages and awards independence of thinking and problem solving approach

 

Class Textbooks / Computing Resources

  Topic-specific handouts will be given for each research problem.

All research problems will be investigated using a scientific programming language preferably Matlab or Octave (open source program similar to Matlab)

 

Final Exam: Take-Home Research Problems

 

Research Problems

Problem #1: Medical Image Manipulation

 

Problem #2: Computer-Aided Diagnosis of Digital Mammography

 

Problem #3: Speckle Reduction

 

Problem #4: Functional MRI Data Processing

 

Problem #5: Microarray Data Analysis

  • Research problem description         

  • Sample Microarray Data Set:    Download To be Posted       

  • Material Handouts: To be Posted

  • Sample Code: To be Posted

 

Supplementary Resources

Matlab Resources

Grading Policy

Research Problem Assignments            

50% (25% x 2)
Final Exam (Research problems + Project) 40% + 10%

  

 

 

 

More Information

Please follow the links here to download course material