Brain imaging demo

General increases in welfare have led to an enormous increase in life expectancy over the last decades in the Western world. This evolution is on-going an it is expected that by 2050 the median age of the population in Europe will have risen from 37.7 years in 2003 to 52.3 years. Along with the ageing population, diseases associated with age (cardiovascular disease, cancer …) are estimated to rise. Among these age related diseases, neurodegenerative diseases such as Alzheimers or Parkinsons have an important contribution. It is estimated that by 2050, 1 in 85 people will suffer from Alzheimer’s disease. Understanding the anatomical and physiological changes that occur in the brain due to these diseases is thereby of paramount importance for the development of new treatments.

At the medical imaging research center in Leuven, engineers and medical doctors make  use of medical images to better understand brain function and anatomy both in healthy and in diseased brains. Medical images allow physicians to look inside the brain and show relevant anatomical or physiological parameters. Processing these medical images in an intelligent way allows gathering as much information as possible about a patient or a group of patients so that we can obtain knowledge about a specific patient or about a specific disease. 

In our demo, we show you the research that engineers are doing to virtually dissect the brain through the use of medical images.

  • On the one hand, image segmentation techniques allow separating clinically relevant structures inside the brain based on anatomical magnetic resonance (MR) images. By looking at these structures for a group of patients, we can obtain insights on the different shapes or appearances of these structures which might be good indications of disease. 
  • On the other hand, diffusion weighted imaging (DWI) is unique in its ability to visualize the white matter fibers connecting the different regions in our brain in vivo and non-invasively.  

Amongst different uses, this information can for instance assist in the preoperative planning for complex brain surgery by showing which connections are affected and which vital connections should be avoided by all means.