PET left ventricular uptake quantification performance using a 3D semiautomatic anatomic – based segmentation approach in type 2 diabetes mellitus patients PET left ventricular uptake quantification performance using a 3D semiautomatic anatomic – based segmentation approach in type 2 diabetes mellitus patients

The aim of this project is to evaluate a well – established 3D atlas – based segmentation approach when quantifying positron emission tomography (PET) left ventricular (LV) uptake in patients with type 2 diabetes mellitus. Performance will be assessed in every American Heart Association segment, ensuring proper 3D LV orientation with anatomical references.

In collaboration with Vall d'Hebron Hospital

Requirements:

  • Candidates must hold a BSc in Biomedical engineering, Telecommunications Engineering, Computer Sciences, Mathematics or related disciplines.
  • Excellent programming skills in at least one of the following languages: Matlab, Python and C++.
  • Good BSc / MSc transcript of records.
  • Interest in medical image processing (PET, CT, MR) and in 3D computer graphics. Prior experience is a plus, but not essential. 
  • Good English command.