Course

Medical Images and Signals (ELE670)

Medical data, in the form of signals and images, is largely used as an important part of the diagnostics. This subject deals with some key techniques for collecting such data. The theme is seen in relation to signal and image processing as well as machine learning, which are as core subjects in the study program, as such methods can be used for automatic segmentation, interpretation and analysis of signals and images. In modern diagnostics, automatic data analysis can be included as decision support.

The the following techniques will be emphasized: Electrocardiography (ECG), Electroencephalography (EEG), Ultrasound, X-ray, Magnetic Resonance Imaging (MR), Computer Tomography (CT), Angiography.


Dette er emnebeskrivelsen for studieåret 2023-2024. Merk at det kan komme endringer.

See course description and exam/assesment information for this semester (2024-2025)

Semesters

Fakta

Emnekode

ELE670

Vekting (stp)

10

Semester undervisningsstart

Autumn

Undervisningsspråk

English

Antall semestre

1

Vurderingssemester

Autumn

Content

This course addresses how some selected medical signals and images are formed and the characteristics of these. This is, to some extent, seen in context with the themes and techniques of signal and image processing and machine learning.

The course will focus on principles, modes of operation, applications, and study of example signals and images for some common techniques for collecting medical diagnostic data. The following techniques will be highlighted:

- Electrocardiography (ECG)

- Electroencephalography (EEG)

- Ultrasound

- X-ray

- Magnetic Resonance Imaging (MR)

- Computer tomography (CT)

- MRI Angiography

Learning outcome

Knowledge: The purpose of the course is to provide students with a technological background insight into techniques for the formation of medical diagnostic important signals and images. Such medical data should then be seen in the context of techniques and knowledge from other subjects. Students will learn about a number of different techniques for collecting medical diagnostic data. The following will be emphasized: Electrocardiography (ECG), electroencephalography (EEG), ultrasound, x-ray, magnetic resonance imaging (MRI), computer tomography (CT), angiography, etc. Students will learn about the principles, operations and applications of these techniques, for example by means of sample signals and images.

Skills: The students should be able to explain the principles behind some techniques for collecting medical diagnostic signals and images. The student should be able to recognize and understand the meaning of specific characteristics from different types of images and signals.

General competence: After taking this course, students will be able to understand the connection between medical diagnostic signals and images and physiological phenomena.

Forkunnskapskrav

Ingen

Anbefalte forkunnskaper

Anatomy and Physiology (BIO110), Signal Processing (ELE500), Image Processing and Computer Vision (ELE510), Machine Learning (ELE520)

Exam

Form of assessment Weight Duration Marks Aid Exam system Withdrawal deadline Exam date
Written exam 1/1 4 Hours Letter grades None permitted 17.11.2023 01.12.2023


Vilkår for å gå opp til eksamen/vurdering

Mandatory assignments
2 mandatory assignments must be approved to get access to exam.

Fagperson(er)

Head of Department:

Tom Ryen

Course coordinator:

Mahdieh Khanmohammadi

Method of work

4-6 lectures a week. Mandatory assignments in addition.

Åpent for

Admission to Single Courses at the Faculty of Science and Technology
Industrial Automation and Signal Processing - Master's Degree Programme - 5 year Robot Technology and Signal Processing - Master's Degree Programme Cybernetics and Applied AI - Master of Science Degree Programme
Exchange programme at Faculty of Science and Technology

Emneevaluering

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Litteratur

Book Bioelectrical signal processing in cardiac and neurological applications Sörnmo, Leif, Amsterdam, Elsevier Academic Press, XIII, 668 s., c2005, isbn:0124375529; 9780124375529, Chapter 1, 2 and 6 of this book will be covered during this course. Book The Essential Physics of Medical Imaging. Bushberg, Jerold T., Philadelphia :, Wolters Kluwer Health, 1 online resource (1501 pages), 2020.; ©2020., isbn:1-9751-0324-6, Chap 1 Chap 2 Chap 3– (up to 3.5) Chap 4 – (selected topics) Chap 5: up to 5.8 Chap 6: 6.1-6.3 Chap 7– (selected topics) Chap 10 Chap 12 Chap 13– (selected topics: up to 13.6) Chap 14
The course description is retrieved from FS (Felles studentsystem). Version 1