3D MRSI-nosologic imaging - Fast multi-modal imaging for diagnosis and therapy assessment of tumour patients
From 01-01-2012 to 31-12-2015
Description
Malignant gliomas are aggressive tumours with poor prognosis. Taking into account the aggressivenature of these tumours and the wide age range at which they occur, malignant gliomas have aconsiderable socio-economic impact.
Magnetic resonance imaging (MRI) is the imaging modality ofchoice in diagnosis, aggressiveness assessment and follow-up of these tumours. However, in themanagement of malignant gliomas current imaging techniques still lack in diagnostic accuracy.
In this project, we aim to develop an imaging protocol in which different advanced MR techniques arecombined within an examination time acceptable for patients.
Furthermore, our goal is to develop(automated) data processing algorithms which address the following areas:
(a) establish an accuratediagnosis,
(b) make an early prognosis on success of therapy,
(c) identify areas of microscopic tumourinfiltration,
(d) identify mechanisms that contribute to success and failure of (new) therapeuticinterventions.
Considering the diversity of imaging and spectroscopic data being collected for each patient over time,fundamental computational problems arise, such as reliable extraction of meaningful features from lowquality spectroscopic data, or optimal combination of all available data sources for robustclassification. Novel data analysis methods will be developed in this project, such as metabolic featureextraction with 3D spatial prior knowledge, and multi-modal approaches to 3D nosologic imaging.
Team
- Uwe Himmerleich, Co-promoter (External)
- Eric Achten, Co-promoter (External)
- Dirk Van Roost, Co-promoter (External)
- Sabine Van Huffel, Promoter
Financing
Funding: FWO - Research Foundation - Flanders
Program/Grant Type: FWO Research Grant - FWO Research Grant
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.