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Carotid Artery Bifurcation Analysis in CT Angiography

The carotid artery bifurcations are two large arterial networks located laterally in the neck and are the major supplier of blood to the brain (Figure 1). A common modality for the diagnosis of the (diseased) carotid artery is Computed Tomography Angiography (CTA) which provides amongst other detailed information of the vessel lumen. Clinical decision making, longitudinal and epidemiological studies concerning the bifurcation often requires a robust lumen segmentation method. We have recently developed such a method [Mann10] which to our knowledge now is ‘state-of-the-art’ in our field. Based on the lumen segmentation, quantitative measures can be derived including geometrical parameters, such as the bifurcation angle and tortuosity, and the degree of stenosis (lumen narrowing). The stenosis degree is an important parameter for e.g. treatment planning.

The goal of this project is the development of robust, accurate and reproducible quantitative measures based on the carotid lumen segmentation.

This project will be carried out in close collaboration with neuroradiologists and will be part of ongoing efforts in our group of building dedicated and advanced workstations to be used in the clinic. As such there is high chance that your contributions will be part of the workstation and therefore will actually be used by clinicians. In addition, a successful completion of the project will give opportunities to publish in international congresses and/or international journals.

Institute

The project will be carried out at the Diagnostic Image Analysis Group (DIAG). DIAG is part of the Department of Radiology at the Radboud University Nijmegen Medical Centre (Nijmegen, the Netherlands) and hosts some of the leading researchers in medical image analysis.

Tasks

  • Literature study
  • Discussion with neuroradiologists about potential interesting quantitative measures of the carotid bifurcation
  • Learning MevisLab, Insight Toolkit and Vascular Modeling Toolkit
  • Data collection and adding specific annotations functionality to workstation
  • Implementation methods for quantification
  • Robustness, accuracy and reproducibility analysis, modification method (this and the previous tasks are typically an iterative process)
  • Writing master thesis

Requirement

We are looking for good students with a background in Computer Science, Physics, Engineering, Biomedical Sciences or similar. Affinity with programming in C++ is strongly preferred.

Information

For more information please contact Rashindra Manniesing.