Life Sciences Life Sciences

Brain segmentation Science Case: Structural brain imaging to helps discovery of disease markers


Life Sciences, Neuroscience

Workflow Links

Freesurfer (different variants):


Magnetic resonance imaging (MRI) provides in-vivo information about brain structure, which is important to identify locations that may be correlated to disease. Characteristics of a brain region, such as shape and volume, can be associated with a phenotype, and serve as "biomarkers". Brain segmentation is also used to facilitate the analysis of brain connectivity between regions, in combination with methods described in the DTI Science Case.
The analysis of brain structural data requires a complex set of steps where the individual regions of the brain are identified, delineated and "labelled", in a process called "brain segmentation". This is a challenging task: manual segmentation is time-consuming, and automated segmentation is very difficult due to brain variability. The Freesurfer software suite is a tool that has been developed and optimized for automated brain segmentation. It includes 30+ steps that have been encapsulated into a workflow; the complete execution takes several hours (12 to 48+ hours). This workflow has been ported for the Dutch grid infrastructure, being offered to the users from a science gateway with intuitive interface.

Scientific Merit

Brain segmentation is a necessary step in any study that uses structural brain scans. As the size of neuroscience and clinical studies grow, also the challenges to perform brain segmentation are increasing. The automated labelling of brain regions empowers neuroscientists and clinical researchers to more easily analyse the characteristics of individual regions, and to develop markers that can be used to detect disease, follow their progress, and control treatment effectiveness along time.


Brain segmentation is a complex process – the figure below illustrates some of the steps involved.
All these steps are encapsulated into the Freesurfer toolbox, which can be activated with different execution options to achieve different goals. We implemented various workflows to run Freesurfer with different options. Below you see the workflow that runs the complete brain segmentation pipeline. Freesurfer execution is split into various steps with checkpointing (although inside one job) to improve robustness of the execution, which can take 1-2 days on the resources of the Dutch grid infrastructure available for our Virtual Organization.


Note: here we describe only one example of various on-going studies that are using the brain segmentation workflow.
Patients with mild cognitive impairment do not always develop dementia. In such cases, abnormal neuropsychological test results may not validly reflect cognitive symptoms due to brain disease, and the usual brain–behaviour relationships may be absent. This study examined the associations between hippocampal volume and memory performance to the results of clinical tests adopted to assess the cognitive condition of 170 patients. The results show that the results obtained by psychological tests correlate well to the two other markers in a group of patients, but they do not correlate well in another group of younger patients. These results have raised various questions about the validity of the tests used in clinical practice to assess the stage or develop prognosis of cognitive impairment diseases.

Related Publications

  1. Rienstra A, Groot PF, Spaan PE, Majoie CB, Nederveen AJ, Walstra GJ, de Jonghe JF, van Gool WA, Olabarriaga SD, Korkhov VV, Schmand B. (2012) Symptom validity testing in memory clinics: Hippocampal-memory associations and relevance for diagnosing mild cognitive impairment. J Clin Exp Neuropsychol. 2012 Dec 11. [Epub ahead of print]
  2. Shayan Shahand, Ammar Benabdelkader,  Mahdi Jaghouri, Jordi Huguet, Mostapha Al Mourabit, Matthan Caan, Antoine van Kampen and Silvia Olabarriaga. A Data-Centric Science Gateway for Computational Neuroscience. Concurrency and Computation: Practice and Experience, epub 14 April 2014



   This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 312579.