MySchool

Department of Engineering
Dean:	Dr. Ármann Gylfason
Email:	ru@ru.is
Website:	http://www.ru.is/tvd
Teachers	View

MSc in Biomedical Engineering
Semesters:	4
Years:	2
ETCS:	120
About major	Í heilbrigðisverkfræði er verkfræðilegum aðferðum beitt til að fást við líffræðileg og læknisfræðileg viðfangsefni, s.s. uppgötvun og þróun nýrrar tækni og aðferða við greiningu og meðferð sjúkdóma. Hér sameinast ólíkar greinar eins og stærðfræði og eðlisfræði við sameindalíffræði og lífeðlisfræði í leit að lausnum heilsufarslegra viðfangsefna. MSc námið er mótað að kröfum Verkfræðingafélags Íslands um fullnaðarmenntun í verkfræði.
Learning Outcomes	View
Education cycle	2
Degree title	MSc in Biomedical Engineering

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	Mandatory course on major		Teaching language
	Optional course on major		Prerequisites for course

Vorönn/Spring 2024

Energy Financial Assessment

SE-833-FA2

ECTS 6

Engineering Optimization

T-423-ENOP

ECTS 6

Sleep

T-424-SLEE

ECTS 6

Decision Analysis for Management

T-603-AKVA

ECTS 6

Internship in Engineering I

T-706-INT1

ECTS 6

Internship in Engineering II

T-706-INT2

ECTS 6

Systems Biology

T-765-SYBI

ECTS 8

Project Management and Strategic Planning

T-803-VERK

ECTS 8

Derivatives and risk management

T-814-DERI

ECTS 8

Creating a Complete Business Plan for a Technical Idea - Entrepreneurship and the Innovation Process

T-814-INNO

ECTS 8

Tissue Engineering and Biomaterials

T-828-TISS

ECTS 8

Graduate Research Opportunities I

T-829-GRO1

ECTS 6

Finite Element Analysis in Engineering

T-844-FEMM

ECTS 8

Digital Transformation of Medical Imaging

T-845-DTMI

ECTS 6

Year

1. year

Semester

Spring 2024

Level of course

6. Second cycle, advanced

Type of course

Elective

Prerequisites

No prerequisites.

Schedule

No schedule found.

Lecturer

Marco Recenti

Content

Medical imaging refers to the process of imaging internal anatomies using various techniques and physical principles. The acquired medical images are now digitalized, regardless of the acquisition physics, and stored and shared in a standardized format known as DICOM. This digitalization opens up new possibilities for the advancement of diagnostics and the understanding of physiological conditions. This 3-week course focuses on Medical Imaging data, particularly Computer Tomography (CT) and Magnetic Resonance Imaging (MRI). The main objectives of the course are Image Segmentation, 3D model rendering, the use of Virtual Reality and 3D printing for surgical planning, Virtual Histology, Medical image feature extraction, and the application of Artificial Intelligence in medical image data. The course will have a strong hands-on approach, with project-based learning on the topics listed.

Learning outcome - Objectives

By the end of the "Digital Transformation of Medical Imaging" course, students will have a solid understanding of medical image data and will be able to work with single pixels to 3D models of anatomy. Specifically, students will learn to use software platforms for segmentation, anatomical analysis, and the design of medical images (such as MIMICS software). Additionally, students will be capable of handling medical images, creating 3D models of anatomical regions, and using advanced segmentation tools to isolate and visualize bones, muscles, and organs. The course will also provide a good understanding and knowledge of 3D printing in healthcare, including data preparation, basics of digital anatomy printing, and applications in surgery. Students will gain insight into virtual reality and augmented reality in a clinical setting, as well as an understanding of pixel value in medical images, including the applications of virtual histology and radiomics.

Course assessment

Group projects

Reading material

No reading material found.

Teaching and learning activities

Lectures, training and hands-on experience, group projects

Language of instruction

English

Neural Engineering

T-863-NEUR

ECTS 8

Wind Power