Skull base lesions cause significant morbidity due to close proximity with critical structures such as the carotid arteries, brain, orbits, optic nerves and chiasm. As a result, skull base surgeries are known for complexity and danger.
The goal of our project is to minimize the risk of surgery and minimize surgical trauma by providing surgeons with the optimal surgical strategy, establishing the best tool pathways and provide rehearsal opportunities. Our search is based on fusion of diverse sources of data, such as medical images and surgeons’ diagnoses) to evaluate risk, feasibility, and possible results of different surgical plans. The software will also provide real-time assistance during the operations.
Our project will focus on the following aspects:
- Fusion of CT, MRI scans and surgeons’ diagnoses, into a visual 3D model.
- Adoption of both surgeons’ experiences and machine learning techniques to automatically search feasible surgical plans, and precisely calculate factors, such as approach angles to the target, travel distances from portals to the target, excision volumes, distances to vital structures and etc., in order to evaluate the plans.
- Providing surgeons with an easy-to-use interface to modify surgical plans in the visual world.
- Providing surgeons easy ways to practice the surgical plans, in the virtual world with virtual instruments, or in the real world with the 3D printed models and real instruments.
- Providing assistance to surgeons during the operation through real-time instrument tracking and warning surgeons if they divert from the adopted plan or are too close to vital structures.
- Providing surgeons an immersive way to replay the operations for future improvement.