Advanced Medical Image Processing

2019-2020

Course Objective

1) learning the difference between experimental environments
such as Matlab and Python, and industry environments such as C++
2) learning the possibilities of C++ for creating classes and processing
methods
3) applying these techniques in advanced medical imaging analysis using
one or more of the following topics:
data structures, interpolation, connected component algorithms,
geometric modelling, optimized algorithms, noise filtering,
wavelet decomposition, machine learning.
4) developing image analysis software tools from concept to algorithm in
C++ .

Course Content

Software for computationally intensive tasks such as dense signal and
image analysis, deep learning and big data applications is usually
written in C++. Even for specialist data science, mathematical and
statistical software such as Python, Matlab and R, the underlying
libraries that ensure optimal efficiency, the low-level processing is
usually implemented as C++ libraries.

This means that knowledge of C++ is often a requirement for working in
these fields of science. The aim of this course is to learn the
development of medical image processing methods in C++ by using modern
language constructs such as classes, standard libraries and templates.
It demonstrates the importance of program syntax and structure to
achieve optimal speed, efficiency and maintainability.

Teaching Methods

lectures, practice sessions, reviews

Method of Assessment

Programming assignment on a specific topic in medical image processing,
including evaluation of the program and reporting on the methods and
results.
Written exam which is accessible after completing the weekly sessions
and the individual assignment.

Target Audience

MNS-master & Master Physcics of Life & Health

Recommended background knowledge

- Medical Imaging (Bachelor physics and bachelor medical
natural sciences)
- Image processing for MNS (Inleiding medische beeldbewerking).
-Some experience with programming, e.g. MatLab.

General Information

Course Code X_422610
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. ir. A.M. Wink
Examiner dr. ir. M.M. Yaqub
Teaching Staff dr. ir. M.M. Yaqub
dr. ir. A.M. Wink

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Computer lab
Target audiences

This course is also available as: