School of Engineering \ Biomedical Engineering
Course Credit
ECTS Credit
Course Type
Instructional Language
Programs that can take the course
Department of Biomedical Engineering
BMM 411 course covers the basic concepts and techniques required for digital analysis and processing of medical images. The course covers basic image processing methods such as image generation, digitization, enhancement, segmentation, feature extraction and classification and their applications in medical imaging systems.
Textbook and / or References
Digital Image Processing (4th Edition), RC Gonzalez, RE Woods, Pearson, 2017
The aim of the BMM 411 course is to teach students the basic concepts and techniques required for digital analysis and processing of medical images and to provide practical skills in the development and application of image processing algorithms. It is aimed that students will be able to analyze and process images obtained from various medical imaging modalities.
1. Understanding and analyzing the features of images obtained from medical imaging systems
2. Understanding digital image processing techniques and algorithms
3. Applying image enhancement and restoration techniques
4. Using image segmentation and feature extraction methods
5. Applying image classification and analysis techniques
6. Effectively using medical image processing software
7. Developing image processing algorithms in MATLAB
8. Using medical image formats and standards (DICOM etc.)
Week 1: Digital Image Fundamentals and Medical Imaging Systems
Week 2: Image Digitization and Sampling
Week 3: Spatial Domain Operations and Filtering
Week 4: Frequency Domain Operations and Transformations
Week 5: Image Enhancement Techniques
Week 6: Image Restoration
Week 7: Morphological Image Processing
Week 8: Image Segmentation
Week 9: Feature Extraction and Identification
Week 10: Image Classification
Week 11: DICOM Standards and Medical Image Formats
Week 12: Advanced Image Processing Techniques
| Tentative Assesment Methods |
| Activities |
Number |
Weight (%) |
| Course Attendance/Participation |
1 |
5% |
| Laboratory |
- |
- |
| Application |
- |
- |
| Homework |
1 |
10% |
| Project |
- |
- |
| Presentation |
- |
- |
| Field Work |
- |
- |
| Internship |
- |
- |
| Course Boards |
- |
- |
| Quiz |
- |
- |
| Midterm Exam |
1 |
35% |
| Final Exam |
1 |
50% |
|
Total |
100% |
| Tentative ECTS-Workload Table |
| Activities |
Number/Weeks |
Duration (Hours) |
Workload |
| Course Hours (first 6 weeks) |
6 |
4 |
24 |
| Course Hours (last 6 weeks) |
6 |
4 |
24 |
| Laboratory |
- |
- |
- |
| Application |
- |
- |
- |
| Homework |
1 |
10 |
10 |
| Project |
- |
- |
- |
| Presentation |
- |
- |
- |
| Field Work |
- |
- |
- |
| Internship |
- |
- |
- |
| Course Boards |
- |
- |
- |
| Preparation for Quiz |
- |
- |
- |
| Preparation for Midterm Exam |
1 |
17 |
17 |
| Final Exam |
1 |
2 |
2 |
| Preparation for Final Exam |
1 |
20 |
20 |
| Study Hours Out of Class (preliminary work, reinforcement, etc.) |
12 |
6 |
72 |
| Total Workload | | |
169 |
| Total Workload / 30 | | |
169 / 30 |
| | |
|
| ECTS Credits of the Course | | |
6 |
|
Program Outcome
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2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
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Course Outcome
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| 1 |
C, A
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| 2 |
A
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| 3 |
A
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A
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| 4 |
A
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A
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| 5 |
A
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A
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| 6 |
A, C
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A
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| 7 |
A
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A
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A
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| 8 |
C, A
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