5.00 credits
30.0 h + 30.0 h
Q1
Teacher(s)
Language
English
Prerequisites
Students are expected to master the following skills: basic mathematical notions (derivatives, coordinate systems) and the Fourier transform, as they are covered within the course LFSAB1106
Main themes
The course deals with the basics of medical imaging, including digital image processing, as well as the main modalities of medical imaging (transmission imaging, emission imaging, ultrasound echography, and magnetic resonance imaging).
Learning outcomes
At the end of this learning unit, the student is able to :  
1 
With respect to the AA referring system defined for the Master in Biomedical Engineering, the course contributes to the development, mastery and assessment of the following skills :
Upon completion of the course, the student will be able to : Part 1 (digital image processing) :
Upon completion of the course, the student will be able to :

Content
The course is divided in three parts :
Part 1 : digital image processing (definition and properties of an image, histogram, spectrum, segmentation, edge detection, filtering, mathematical morphology, registration)
Part 2 : magnetic resonance imaging and ultrasound imaging (linear systems : convolution, point spread function, Fourier transform, sampling ; image reconstruction : Radon transform, filtered backprojection, algebraic reconstruction)
Part 3 : transmission imaging (radiography and computerized tomography) and emission imaging (scintigraphy, SPECT and PET)
Part 1 : digital image processing (definition and properties of an image, histogram, spectrum, segmentation, edge detection, filtering, mathematical morphology, registration)
Part 2 : magnetic resonance imaging and ultrasound imaging (linear systems : convolution, point spread function, Fourier transform, sampling ; image reconstruction : Radon transform, filtered backprojection, algebraic reconstruction)
Part 3 : transmission imaging (radiography and computerized tomography) and emission imaging (scintigraphy, SPECT and PET)
Teaching methods
The course consists of 13 lectures in English, three sessions of exercises (mostly reminders or introductory exercises), and three small projects (challenges). For each challenge, groups of two students must submit a report. These reports are evaluated. During a debriefing session, the most commonly encountered issues will be presented and discussed between the teacher and the students. A visit of medical imaging facilities in SaintLuc University Hospital (Brussels) completes the program. All activities can switch to comodal or distancial depending on sanitary conditions.
Evaluation methods
Evaluation of the exercises (challenges only)
Each challenge report will be given a note. The global note for all challenges affects the final evaluation (see below). The introductory exercises that preceed the challenges will be evaluated in a formative way with no impact on the final evaluation. The submission of all challenge reports is mandatory to be admitted to the oral examination for part 1 of the course.
Evaluation of the learning outcomes
The students will be evaluated individually and orally (presential or distancial) on the basis of the contents and learning outcomes mentioned above. The oral examination (in French or English, up to the student) will address :
Part 1 (10 points out of 20, image processing) : the student must answer two questions dealing with the methods and algorithms used in the challenges (see below). Starting from a simple problem (which can be solved with a pen and paper), the student should be able to justify his choices. On 10 points, one half results from the evaluation of the challenge reports, the other half corresponding to the two questions.
Part 2 (5 points out of 20, IRM and ultrasound imaging ) : the student must answer two questions (oral examination with written preparation)
Part 3 (5 pointsout of 20, imaging modalities using ionizing radiation) : the student must answer two questions (oral examination with written preparation).
Each challenge report will be given a note. The global note for all challenges affects the final evaluation (see below). The introductory exercises that preceed the challenges will be evaluated in a formative way with no impact on the final evaluation. The submission of all challenge reports is mandatory to be admitted to the oral examination for part 1 of the course.
Evaluation of the learning outcomes
The students will be evaluated individually and orally (presential or distancial) on the basis of the contents and learning outcomes mentioned above. The oral examination (in French or English, up to the student) will address :
Part 1 (10 points out of 20, image processing) : the student must answer two questions dealing with the methods and algorithms used in the challenges (see below). Starting from a simple problem (which can be solved with a pen and paper), the student should be able to justify his choices. On 10 points, one half results from the evaluation of the challenge reports, the other half corresponding to the two questions.
Part 2 (5 points out of 20, IRM and ultrasound imaging ) : the student must answer two questions (oral examination with written preparation)
Part 3 (5 pointsout of 20, imaging modalities using ionizing radiation) : the student must answer two questions (oral examination with written preparation).
Other information
The first two sessions of exercise are organized in the computer room
Online resources
Bibliography
Support de cours :
Partie 1 : transparents.
Parties 2 et 3 : transparents et syllabus.
Les documents du cours sont disponibles sur Moodle.
Partie 1 : transparents.
Parties 2 et 3 : transparents et syllabus.
Les documents du cours sont disponibles sur Moodle.
Teaching materials
 Transparents et notes relatives aux séances de cours disponibles sur Moodle
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Electrical Engineering
Master [120] in Computer Science and Engineering
Master [120] in Statistics: Biostatistics
Master [120] in Biomedical Engineering
Master [120] in Physics
Certificat universitaire en physique d'hôpital
Master [120] in Mathematical Engineering