Post-Doctoral Research Visit F/M Real-time vessel localization in fluoroscopy for autonomous endovascular navigation

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Contract type : Fixed-term contract

Level of qualifications required : PhD or equivalent

Fonction : Post-Doctoral Research Visit

Context

The MIMESIS team is at the forefront of innovation in the fields of scientific computing, machine learning, medical imaging, and control. We are an interdisciplinary team that collaborates closely with clinicians to develop new technologies that can help improve healthcare, in particular through computer-assisted interventions. Our core research activities take place in the biomechanical modeling of soft tissue and developing novel numerical methods for real-time computation. Our research results pave the way towards augmented reality during interventions, autonomous medical robotics, and creating digital twins for personalized operation planning.

MIMESIS and LN Robotics, a South Korean medical robotics company, previously collaborated on a research project on autonomous endovascular navigation. LN Robotics has developed AVIAR, a robotized intervention system that reduces clinician radiation exposure during cardiovascular procedures. Building on their successful initial collaboration, both partners are now launching a new project to integrate artificial intelligence capabilities into AVIAR. This project aims to enhance fluoroscopic guidance through real-time vessel visualization and enable automated navigation. Our team's state-of-the-art vessel localization method will be central to this effort, with this postdoctoral position focused on advancing it toward clinical application.

Assignment

In fluoroscopy-guided endovascular interventions, vessel visualization traditionally relies on contrast agent injection. However, these agents are toxic at high doses and cannot be continuously injected. To overcome this limitation, we recently propose a solution based on deformable 2D-3D registration. Our method uses a preoperative 3D model of the vessels and updates it in real-time to provide clinicians with continuous vessel visualization throughout the procedure. Accurate and continuous vessel tracking is fundamental for autonomous endovascular interventions, as it enables precise robotic navigation without repeated contrast injections while ensuring safety through constant visual feedback.

Extracting vessel information from fluoroscopic images presents significant challenges: poor image contrast, limited 2D perspective, and scarcity of clinical data for training and validating deep learning approaches. Our deformable 2D-3D registration method was developed with these limitations in mind, and demonstrated promising results. The postdoctoral researcher will build upon these initial successes to develop a robust vessel tracking method suitable for clinical translation. This ambitious project requires innovative solutions at the intersection of computer vision, deep learning, and medical imaging. Success will depend on close collaboration with engineers and clinical partners to ensure that the developed method meets the robustness, accuracy, and real-time performance requirements of interventional practice

Main activities

The successful candidate will work on improving and validating our deep learning-based deformable 2D-3D vessel registration method. Key objectives include:

  1. Enhancing robustness and accuracy of vessel tracking under challenging clinical conditions (motion artifacts, varying contrast, overlapping structures)
  2. Integrating vessel tracking in the AVIAR robotic system
  3. Developing experimental validation protocols
  4. Extending the method to handle catheter tracking
  5. Creating safety measures for reliable autonomous navigation

Skills

Technical skills and level required:

  • Sound knowledge of modern computer vision techniques
  • Sound knowledge of Machine Learning / Deep Learning with Artificial Neural Networks
  • Basic knowledge of medical imaging modalities

Software development skills : Python programming, Pytorch.

Relational skills : team worker (verbal communication, active listening, motivation and commitment).

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage

Remuneration

2788 € gross/month