Internship: Data science/AI, medical foundation models for accelerating labeling

il y a 2 semaines

Montpellier, Occitanie, France SIM&CURE Temps plein

Founded in 2014, Sim&Cure is French digital start-up focused on improving neurovascular treatments of cerebral aneurysm with a proprietary software suite. The Sim&Size software is a Class II medical device with CE mark and FDA clearance that has already been used to treat more than 10,000+ patients in 500+ hospitals in the world.

Through several modules, Sim&Size is a software suite that provides to the physician a 3D visualization of medical images and a computational model of neurovascular implantable medical devices (IMDs). The therapeutic strategy is the most important step of this disease treatment and Sim&Size is now part of it by being efficient, safe, and reproducible. Computational modeling of specific devices in the anatomy of a patient helps the physician to achieve the intended outcome of the intervention.

Context and Issues

In the field of medical imaging, manual annotation of 3D images represents a major challenge, requiring considerable time and specific expertise from radiologists, which limits and slows down the development of advanced clinical AI models. The emergence of foundational models for medical imaging in computer vision, such as VISTA3D, opens up new perspectives for supporting annotation tasks.

Internship Objectives

Evaluate the capabilities of a foundational model for medical imaging and develop an interface in order to evaluate assisted annotation process (speed, quality).

The project will be structured in the following way:

  • State of the art of medical foundational models
  • Simple and semi-supervised inferences with chosen model
  • Development of the visualization/annotation interface
  • Evaluation of annotations produced for training internal segmentation models

Developed Skills

  • Deep learning: Self-supervised learning, semi-supervised learning, segmentation models
  • Libraries: Torch, Monai, Trames, Dash, Pyvista
  • Cloud: AWS
  • Deep learning in a medical context

  • Medical imaging

  • Strong foundations in Python and software development (must have)

  • Knowledge in machine learning and Deep Learning (must have)
  • Interest in medical AI applications, particularly computer vision
  • Rigorous and proactive (must have)
  • Experience with "interface" libraries (Trames, PyVista, Streamlit or others)
  • Initial experience (internship / project) in a start-up environment (nice to have)

Level: Master's Degree (final year) / Engineering school

Duration: 4-6 months

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