Information Package / Course Catalogue
Medical Image Processing
Course Code: MCS520
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: English
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

This course is intended to introduce methods and techniques of image processing for image analysis, pattern recognition and visualization for supporting computer aided diagnostics and therapy.

Course Content

The content of this course covers topics starting with generating medical images, registration and segmentation of medical image data, quantitative image analysis, classification and image recognition up to visualization medical image data and computer supported diagnostics and therapy.

Name of Lecturer(s)
Lec. Samsun Mustafa BAŞARICI
Learning Outcomes
1.Explain the basic terms related to medical images and their generation.
2.Understand the foundations of image processing systems supporting diagnosis and therapy.
3.Assess and perform medical image registration.
4.Evaluate and apply medical image segmentation.
5.Develop a strong understanding for quantitative image analysis, classification and image recognition.
Recommended or Required Reading
1.Thomas M. Deserno, “Biomedical Image Processing”, Springer, 2013, ISBN: 978-3642267307
2.John C. Russ, “The Image Processing Handbook, 6th Ed.”, CRC Press Inc, 2011, ISBN: 978-1439840450
3.John L. Semmlow, Benjamin Griffel, “Biosignal and Medical Image Processing, 3rd Ed. ”, CRC Press Inc, 2014, ISBN: 978-1466567368
4.Ryszard Tadeusiewicz, “Medical Image Understanding Technology: Artificial Intelligence and Soft-Computing for Image Understanding”, Springer, 2004, ISBN: 978-3540219859
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction, Image producing methods and techniques in medicine
Week 2 - Theoretical
Image producing methods and techniques in medicine (cont.)
Week 3 - Theoretical
Basics of image processing systems for diagnosis and therapy support
Week 4 - Theoretical
Registration of medical image data
Week 5 - Theoretical
Registration of medical image data (cont.)
Week 6 - Theoretical
Segmentation of medical image data
Week 7 - Theoretical
Segmentation of medical image data (cont.)
Week 8 - Theoretical
Quantitative image analysis
Week 9 - Theoretical
Classification and image recognition
Week 10 - Theoretical
Classification and image recognition (cont.)
Week 11 - Theoretical
Feature selection and transformation
Week 12 - Theoretical
Visualization of medical image data
Week 13 - Theoretical
Computer aided diagnosis and therapy
Week 14 - Theoretical
Presentation of projects
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%10
Final Examination1%70
Term Assignment1%20
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142370
Term Project1401050
Midterm Examination135338
Final Examination145348
TOTAL WORKLOAD (hours)206
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
OÇ-1
3
3
3
3
4
3
4
3
4
OÇ-2
4
4
4
3
5
4
3
4
3
OÇ-3
3
3
5
5
5
4
3
5
5
OÇ-4
3
3
3
3
4
3
4
3
3
OÇ-5
4
4
4
3
5
4
3
4
3
Adnan Menderes University - Information Package / Course Catalogue
2026