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Fully funded Phd position in Augmented Reality for Ultrasound Imaging

Programme d'études visé
Doctorat
Domaines de recherche
Technologies de la santé
Systèmes logiciels, multimédia et cybersécurité
Financement
30K$ per year for 4 years
Autres informations

Interested candidates sent a single PDF file (do not zip it) to Professor Simon Drouin, including:

  • A cover letter detailing their research interests and explaining how their qualifications align with the specific requirements of the position.
  • A CV, including a full list of publications.
  • A copy of academic transcripts.
  • Contact information for 2 references.
Personne à contacter

Background: Ultrasound (US) imaging is rapidly becoming a cornerstone of modern healthcare, delivering fast, safe, and accessible imaging at a fraction of the cost of traditional technologies. Yet, the usability of US is often undercut by operator skill, variability of image quality, and the unfamiliar orientation and 2D nature of the image. The proposed PhD project will aim at improving US imaging usability by integrating a US device with an augmented reality (AR) display, enabling a more intuitive, in-situ visualization of the patient’s anatomy.

Project description: A doctoral research position is available at ÉTS. The successful candidate will work with a team of engineers, computer scientists and clinicians to develop advanced AR visualization methods that will improve 3D ultrasound interpretation. The project will involve combining advanced computer vision techniques to track the US probe and the patient, advanced machine learning methods to analyse US images and provide real-time feedback during ultrasound exams, and computer graphics concepts to ensure that the AR display is easy to interpret and perceptually sound. The development of the novel AR-US system will be done in close collaboration with medical teams at University of Montreal Hospital Center (CHUM) to ensure clinical relevance.

Connaissances requises

Candidate should have a master’s degree in Computer Science, Electrical and Computer Engineering, Biomedical Engineering or related field (or be graduating shortly) with strong analytical and programming skills (C, C++, Python), ability to work independently, good communication skills and research experience in computational image analysis methods. Previous experience with medical image processing, image-guided surgery, graphics API (OpenGL, DirectX, Vulkan), game engines (Unity, UnReal), iOS/Android, VTK, ITK and/or 3D Slicer is a plus.