GRADUATE SCHOOL

M.SC. in Bioengineering (With Thesis)

BEN 522 | Course Introduction and Application Information

Course Name
Advanced Medical Image Analysis
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
BEN 522
Fall/Spring
3
0
3
7.5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second 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 and basic and advanced image processing algorithms.

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction Course notes
2 Medical Imaging: X-Ray, BT, PET and SPECT Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 15
3 Medical Imaging:Ultrasound and MRI Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 15
4 Storage, Archiving and Communication of Medical Images and Medical Image Formats Course notes
5 Visualization of Medical Images Course notes
6 Basics of Medical Image Analysis Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 12
7 Midterm
8 Segmentation of Medical Images - I Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 14
9 Segmentation of Medical Images – II Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 14
10 Registration of Medical Images - I Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 13
11 Registration of Medical Images - II Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 13
12 Classification and Detection in Medical Images - I Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 16
13 Classification and Detection in Medical Images - II Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, Chp. 17
14 Object Tracking in Medical Images Course notes
15 Review of the semester
16 Final Exam

 

Course Notes/Textbooks

Biosignal and Medical Image Processing, John L. Semmlow and Benjamin Griffel, CRC Press – 3rd edition (2014). ISBN: 1466567368

Suggested Readings/Materials

Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis, J. Michael Fitzpatrick and Milan Sonka, SPIE—1st edition (2009).

Paul Suetens, "Fundamentals of Medical Imaging", Second Edition, Cambridge University Press, ISBN: 0521519152, 2009.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
30
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
2
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
6
84
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
15
0
Project
1
40
40
Seminar / Workshop
0
Oral Exam
0
Midterms
1
18
18
Final Exam
1
20
20
    Total
210

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To be able to have adequate knowledge in Mathematics, Life Sciences and Bioengineering; to be able to use theoretical and applied information in these areas to model and solve Bioengineering problems.

X
2

To be able to use scientific methods to complete and apply information from uncertain, limited or incomplete data; to be able to combine and use information from related disciplines.

X
3

To be able to design and apply theoretical, experimental and model-based research; to be able to solve complex problems in such processes.

X
4

Being able to utilize Natural Sciences and Bioengineering principles to design systems, devices and processes.

X
5

To be able to follow and apply new developments and technologies in the field of Bioengineering.

X
6

To be able to work effectively in multi-disciplinary teams within the discipline of Bioengineering; to be able to exhibit individual work.

X
7

To be able to have the knowledge about the social, environmental, health, security and law implications of Bioengineering applications, to be able to have the knowledge to manage projects and business applications, and to be able to be aware of their limitations in professional life.

X
8

To be able to have the social, scientific and ethical values ​​in the stages of collection, interpretation, dissemination and application of data related to the field of Bioengineering.

X
9

To be able to prepare an original thesis/term project in accordance with the criteria related to the field of Bioengineering.

10

To be able to follow information about Bioengineering in a foreign language and to be able to participate in discussions in academic environments.

X
11

To be able to improve the acquired knowledge, skills and qualifications for social and universal purposes regarding the studied area.

X
12

To be able to recognize regional and global issues/problems, and to be able to develop solutions based on research and scientific evidence related to Bioengineering.

X

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

 


Izmir University of Economics
is an establishment of
izto logo
Izmir Chamber of Commerce Health and Education Foundation.
ieu logo

Sakarya Street No:156
35330 Balçova - İzmir / Turkey

kampus izmir

Follow Us

İEU © All rights reserved.