FACULTY OF ENGINEERING

Department of Genetics and Bioengineering

BME 404 | Course Introduction and Application Information

Course Name
Biomedical Image Processing
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
BME 404
Fall/Spring
2
2
3
5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives The aim of this course is to provide students with a knowledge and understanding of fundamental principles of medical image enhancement, registration, classification, and segmentation.
Learning Outcomes The students who succeeded in this course;
  • Define the principles and main technical aspects of medical imaging analysis
  • Explain the need for basic image processing techniques.
  • Describe fundamental approaches for enhancement of medical images
  • Describe fundamental approaches for segmentation of medical images.
  • Describe fundamental approaches for registration of medical images.
Course Description Principles of acquisition, storage, visualization, and processing of medical image data. Sampling and quantization. Picture archiving and communication systems, Medical image formats. Basic and advanced image processing algorithms.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction and Overview Lecture notes
2 Medical Imaging Technology Chp 1, 6-8. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.1, SPIE Press
3 Medical Image Acquisition, Sampling, and Quantization Lecture notes
4 Medical Image Storage, Archiving and Communication Systems and Formats Chp 8-9. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.3, SPIE Press
5 Medical Image Processing, Enhancement, Filtering Chp 4-5. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.2, SPIE Press
6 Medical Image Segmentation - I Chp 2-3. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.2, SPIE Press
7 Medical Image Segmentation - II Chp 2-3. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.2, SPIE Press
8 Review and Midterm Examination
9 Medical Image Registration - I Chp 8. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.2, SPIE Press
10 Medical Image Registration - II Chp 8. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.2, SPIE Press
11 Medical Image Visualization Chp 1. "Handbook of Medical Imaging", Sonka and Fitzpatrick, Vol.3, SPIE Press
12 Medical Image Compression Lecture notes
13 Medical Image Search and Retrieval Lecture notes
14 Other Applications of Medical Image Analysis Lecture notes
15 Evaluation of Term Projects
16 Final

 

Course Notes/Textbooks Handbook of Medical Imaging, Medical Image Processing and Analysis (2009) by Milan Sonka and J. Michael Fitzpatrick, SPIE Press, ISBN: 0819477605.
Suggested Readings/Materials Biomedical Signal and Image Processing (2005) by Kayvan Najarian and Robert Splinter, CRC Press, ISBN: 0849320992.\\nDigital Image Processing for Medical Applications (2009) by Geoff Dougherty, Cambridge Univ. Press, ISBN: 0521860857.\\nMedical Imaging Signals and Systems (2005) by Jerry L. Prince and Jonathan Links, Pearson, ISBN: 0130653535.\\nBiosignal and Medical Image Processing (2008) by John L. Semmlow, CRC Press, ISBN: 1420062301. Lecture slides will be distributed as softcopy.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
4
20
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
5
Project
1
15
Seminar / Workshop
Oral Exams
Midterm
1
20
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
60
Weighting of End-of-Semester Activities on the Final Grade
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
16
2
32
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
1
12
12
Project
1
12
12
Seminar / Workshop
0
Oral Exam
0
Midterms
1
12
12
Final Exam
1
18
18
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Genetics and Bioengineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

2

To be able to identify, define, formulate, and solve complex Genetics and Bioengineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Genetics and Bioengineering applications; to be able to use information technologies effectively.

5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Genetics and Bioengineering research topics.

6

To be able to work efficiently in Genetics and Bioengineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Genetics and Bioengineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Genetics and Bioengineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in Genetics and Bioengineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Genetics and Bioengineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Genetics and Bioengineering.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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