3D real-time low field MRI guidance of neurosurgical robots

MRI-guided neurosurgery is a procedure used to treat conditions related to the nervous system, including brain tumours, epilepsy seizures and movement disorders. MRI provides excellent soft-tissue contrast, and can be used for navigation, targeting, and monitoring of the safety and efficacy of the procedure. MRI-compatible surgical robotic systems have the potential to ensure effectiveness, safety, and speed of MRI-guided neurosurgical procedures. Furthermore, the reemergence of low-field MRI systems offers a favourable environment for the development of MRI-compatible surgical robots, patient access, and cost effectiveness. Real-time imaging with fast reconstruction times is required for intra-operative MRI guidance of robotic systems. Current real-time sequences are limited to 2D imaging; however, 3D imaging techniques have the potential of offering an increased spatial coverage, more precise guidance, and improved safety compared to 2D imaging. Furthermore, 3D imaging has the advantage of higher SNR which is particularly advantageous at lower field strengths. This PhD project will aim to develop novel 3D real-time MRI acquisition, and AI-based reconstruction and tracking/detection methods for image-guidance of robotic systems in MRI-guided neurosurgery at low field (0.55T).