Biomedical Image Processing
| Title | Επεξεργασία Βιοϊατρικής Εικόνας / Biomedical Image Processing |
| Code | MEI005 |
| Faculty | Health Sciences |
| School | Medicine |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter |
| Coordinator | Petros Daras |
| Common | No |
| Status | Active |
| Course ID | 600021931 |
Programme of Study: PMS "Iatrikī Mīchanikī kai Plīroforikī" (2022-sīmera)
Registered students: 9
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 6 |
| Academic Year | 2024 – 2025 |
| Class Period | Winter |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600265086
|
Course Type 2021
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600265086
Language of Instruction
- English (Instruction, Examination)
Learning Outcomes
The purpose of this course is for students to learn about the basics of digital bio-medical image processing so as to better understand its necessity and the reasons that make the subject of particular interest with respect to both research and application.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Work in teams
- Work in an interdisciplinary team
- Generate new research ideas
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to Medical Imaging Processing
2. Introduction to Neural Networks
3. Introduction to Medical Image Segmentation
4. Medical Image Visualisation
5. Medical Image Registration
6. Object Detection In Medical Images
7. Advanced Techniques in Deep Learning: Fully Convolutional Neural Networks
8. Advanced Techniques in Deep Learning: Reinforcment Learning
9. Seminar: Bioinformatics
10. Seminar: Sign Language Detection
Keywords
Processing, Segmentation, Neural Nets
Educational Material Types
- Notes
- Slide presentations
- Multimedia
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 22 | 0.9 | |||
| Seminars | 4 | 0.2 | |||
| Reading Assigment | 64 | 2.6 | ✓ | ||
| Exams | 60 | 2.4 | ✓ | ||
| Total | 150 | 6 |
Student Assessment
Description
Assessment:
- Papers' analyses and presentations 30%
- Exams 70%
Student Assessment methods
- Written Exam with Short Answer Questions (Formative)
- Written Exam with Extended Answer Questions (Formative)
- Written Assignment (Formative)
Bibliography
Additional bibliography for study
R. Gonzalez and R. Woods, Digital Image Processing, 2nd edition, Prentice Hall, 2002.
- Image Processing Toolbox, Users Version 4, 2003, The Mathworks
- R. Gonzalez, R. Woods, S.Eddins, Digital Image Processing using MATLAB, Prentice Hall 2004.
- I. Πήττας, Επεξεργασία Εικόνας
- N. Kalouptsidis, Signal Processing Systems, Theory and Design, John Wiley, 1997
- Lim, 2-D signal and image processing, Prentice Hall, 1990.
- Περιοδικα¨IEEE Trans. on Medical Imaging,
+ IEEE Trans. on Pattern Analysis and Machine Intelligence
+ NeuroImage, Elsevier
+ Medical Image Analysis, Elsevier
Last Update
24-11-2023
