About ETRO  |  News  |  Events  |  Vacancies  |  Contact  
Home Research Education Industry Publications About ETRO

Master theses

Current and past ideas and concepts for Master Theses.

Investigating the influence of radiomics features in the performance of a Computer Aided Diagnosis system for lung cancer.


Lung nodules are an important indicator of lung cancer. Computer Aided Detection and Diagnosis (CAD) systems have been developed to identify them in lung CT images. The first goal of such a system is to identify many regions as potential threats. A second system should be then applied in order to classify these regions of interest as real nodules or benign findings. This step is known as false positive reduction step. This thesis will focus on this part of the system that involves the implementation of a machine learning pipeline. The first step will regard the extraction and analysis of a large number of features called radiomic features. The next steps will include selection of relevant features and classification of the candidate findings.

Kind of work

1. Literature review of (i) the medical problem, (ii) existing computer aided diagnosis systems and (iii) radiomics
2. Extraction and analysis of radiomics features
3. Investigating the influence of different machine learning methods
a. Implementation of feature selection algorithms
b. Implementation of classification algorithms
4. Comparing and analyzing the results
5. Thesis writing and presentation

Framework of the Thesis

Relevant literature:

Number of Students


Expected Student Profile

Interest in computer aided diagnosis systems and machine learning
Good knowledge of Python and MATLAB


Prof. Dr. Bart Jansen

+32 (0)2 629 1034

more info


Dr. Ir. Evgenia Papavasileiou

+32 (0)2 629 1687

more info


- Contact person




- Contact person

- Thesis proposals

- ETRO Courses

- Contact person

- Spin-offs

- Know How

- Journals

- Conferences

- Books

- Vacancies

- News

- Events

- Press


ETRO Department

Tel: +32 2 629 29 30

©2022 • Vrije Universiteit Brussel • ETRO Dept. • Pleinlaan 2 • 1050 Brussels • Tel: +32 2 629 2930 (secretariat) • Fax: +32 2 629 2883 • WebmasterDisclaimer